Recent developments in the UK Using the indices and the underpinning data Tom Oxford Consultants for Social Inclusion (OCSI) David McLennan.

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Presentation transcript:

Recent developments in the UK Using the indices and the underpinning data Tom Oxford Consultants for Social Inclusion (OCSI) David McLennan University of Oxford

Overview The English Indices of Deprivation –Methodology & structure –One domain in detail – Education, Skills & Training –Administrative & census data sources How the Indices & underpinning data are used –National & local examples –Summary of uses –A driver for increased use of evidence-based policy and services The potential for South African crime domain

The English Indices of Deprivation

English Indices of Deprivation Long history of Indices in the UK, for allocating and targeting resources Since the late 1990s, major programmes of regeneration aimed at ‘closing the gap’ –To tackle inequality of both opportunity and outcome –Challenging national ambitions & targets – for example “people should not be seriously disadvantaged by where they live” Indices of Deprivation 2000 and updates used to support area-based programmes & interventions –Targeting resources, perhaps 1-2% of central government spend –Focus on ‘deprived areas’, as part of broad range of approaches –Renewed emphasis on ‘evidence-based policy’

English Indices – structure Index of Multiple Deprivation based on seven domains –Income –Employment –Education, skills and training –Health deprivation and disability –Crime –Barriers to housing and services –Living environment deprivation. Each domain is based on a set of indicators –40 indicators in total, from different sources Single overview indicator of how all areas compare on deprivation levels

English Indices of Deprivation – methodology Indicators are combined into domains –Standardised to enable comparison –Factor analysis used to combine indicators Domains combined into the headline Index of Multiple Deprivation –Standardised to enable comparison Statistical techniques –Shrinkage, for small area data reliability –Exponential transformation, to minimise ‘cancellation’ –Ranking, to allow indicators & domains to be combined –Weighting, to give greater impact to more important domains

Education, Skills & Training Domain “The lack of attainment & skills in the local population” 2 sub-domainsSet of indicators

Education, Skills & Training indicators IndicatorHow is it measured? Adults with no or low qualifications UK Census, self-reported English language proficiencyUK Census, self-reported Pupil attainment for national ‘Key Stage’ exams School pupil exam results, by pupil home address Secondary school absenceSchool registers, by pupil home address Staying on in education (beyond 16) 17 year olds receiving government benefit payable to those in education Entry to Higher Education Successful entry to University/ HE, by address of application

Administrative & census data sources UK Census is a very rich source of small area data –Carefully designed question set, rigorous survey –Cross-tabulated data eg unemployment by age / gender / ethnicity –But … only updated every 10 years –And, does not ask Income questions ‘Administrative’ data collected as by-product of some other process (school exams, benefit payment etc) –Rich detail on wide variety of issues relevant to deprivation –Regularly updated, and easier (cheaper) to collect –Data can be improved over time, eg linking school exam results to pupils homes (rather than schools) –But … data changes; eg changes to exams, benefit eligibility etc –Also, multiple data sources are not linked – so do not typically allow multi-dimensional analysis on single individuals

How the English Indices & underpinning data are used

How the Indices & underpinning data are used – national examples Central government funding allocations, including: –‘Mainstream’ funding - NHS Area & Local Government formulae –‘Top-up’ funding for regional/ local regeneration pots Direct funding for targeted large-scale national regeneration programmes –Neighbourhood Regeneration Fund & Working Neighbourhoods Fund – “helping turn around the hardest hit areas” Indirect use in commissioning and targeting –Sure Start & children’s centres –Big Lottery – 14 billion rand per year on ‘Good causes’ –New Deal for Communities, 10 year 200 billion rand programme Tax relief on property & land transactions

How the Indices & underpinning data are used – local examples Local programmes and funds –Local Authority controlled grants and funds –Commissioned services & delivery; Benefit take-up programmes Targeting funds to voluntary (non-profit) organisations –London Councils funding for organisations across the capital –Local Authority support funding –Bids to provide services typically highlight impact in deprived areas Social housing associations – community investment –100s of (independent) housing organisations –Total funding similar to Big Lottery (15 billion rand per year)

A driver for increased use of evidence- based policy and services Indices of Deprivation and Census have underpinned widespread increase in the use of data & analysis –Supporting national and local programmes & services –Pressure on government to make ‘open data’ available Better understanding at senior level of the need for better evidence (chief executive, directors) –Pushed by national demands for evidence-base, and local needs for information Building research, data and skills capacity –Neighbourhood renewal partnership capacity building –Local data systems –Local Improvement Advisors & other support

Summary of uses for the English Indices of Deprivation 1.Funding and commissioning – relatively big sums 2.‘Unexpected consequences’. Positive incentives for some projects, eg increasing benefits take-up 3.Impact of programmes – changes in deprived areas 4.Research & analysis – potential driver of other outcomes (particularly health research) 5.Dissemination and transparency – “what services and programmes are we running in which areas”

The potential for South African crime domain [ Handover to David McLennan ]

Recent developments in the UK Using the indices and the underpinning data Tom Oxford Consultants for Social Inclusion (OCSI) David McLennan University of Oxford