1. Better Information for Regional Government Marie Cruddas, Minda Phillips & Pete Brodie, ONS. Presented by Martin Brand, ONS Methodology Directorate

2. Outline of Presentation The Neighbourhood Statistics Programme –Background –Topics and data sources –Estimating for small areas Allsopp Review –Background –Recommendations –Developments

3. Neighbourhood Statistics - The Need “… anyone can wander through some of these [deprived] areas and know that something is very badly wrong – but the government has never set out to record or analyse the issues in a comprehensive way.…” PAT 18 Report on Better Information

4. What is Neighbourhood Statistics? A service designed to meet the needs of the National Strategy for Neighbourhood Renewal. “The absence of information about neighbourhoods has produced a series of failings at national, local and community level…policies can easily be misdesigned or mistargeted….and important trends have been missed”.

5. What does Neighbourhood Statistics offer? Publicly available internet access to - Neighbourhood Profiles; Thematically map any data; Point location of services; Library of datasets to view or download; Pick and mix variables from different datasets; Time series analysis; and Create your own area. http://neighbourhood.statistics.gov.uk

6. Topics and data sources 13 main topic areas relating to deprivation. Two examples are; 1. Work Deprivation: Business and economic activity data, work-related benefits claimants, and participation on government training programmes. Data sets include; –Benefit claimants (administative source) –Occupational group (Census) –Counts of enterprises by industry group (Business Register) –Employment rate (Survey)

9. Topics and data sources 2. Economic Deprivation: Data relating to economic activity, poverty and the provision of selected welfare benefits. Data sets include; –Income support claimants (administrative source) –Child benefit claimants (administrative source) –Household income (model based estimates)

10. Model-Based Estimation for Small Areas Census, survey and administrative sources do not cover all requirements Statistical techniques used to produce estimates for small areas when "standard" survey estimates for these areas are unreliable or cannot be calculated. - Ghosh and Rao (1994) and Rao (1999). Use models to "borrow strength" over space, over time or from correlation with auxiliary information provided by administrative or Census sources

11. Small Area Estimates of Income Survey Data –Family Resource Survey (FRS) –Household total and net income –Sample size 21,000 households in 3,375 wards Covariate Data –2001 Census –Department for Work and Pensions benefit claimant count data –HM Land Registry dwelling price data –Council tax data –Regional indicators Estimation –Multi-level model –Model-based estimates for 9,275 wards –Published as experimental statistics

12. NeSS - Future Direction and Developments ‘First Stop Shop’; Increased use of administrative data; Improved analytical capacity; Ongoing improvements to usability; and Use of new technologies.

13. Allsopp Review – 2004 Review of Statistics for Economic Policymaking –To assess the demand for and provision of regional information, and –examine whether official economic statistics adequately reflect changing UK economic structure

14. Allsopp Review – 2004 Recommendations relating to regional statistics Improvements to regional data –Good quality and timely estimates of annual Gross Value Added for regions Make more use of administrative data Expand micro-economic and sub-regional data through the infrastructure used by NeSS Give greater access to the ONS business related administrative data

15. Developments Development of new Business Register Employment Survey (BRES) –to inform the register –to provide the basis for the annual employment estimates Access to Administrative Data for small businesses, eg –Corporation Tax –VAT

16. Developments - BRES Improved data –new questionnaire to improve data quality –employment size and turnover measure at LU level –Improved validation and imputation Improved stratification –complexity of business –FTE instead of headcount –“unusual” businesses defined using admin data Improved regional estimation –marginal level calibration –winsorisation

17. Developments - Regional Statisticians ONS has established a presence in the 9 English regions. work with regional partners on collaborative projects and provide advice of the use of official statistics; gather information to improve the quality of ONS data and processes; quality assure final estimates of regional Gross Value Added (GVA); help improve the quality of the Inter-Departmental Business Register (IDBR) and business survey data; provide access to IDBR data; and provide a first point of ONS contact for key regional bodies.

18. Thank you