Better Information for Regional Government

Marie Cruddas, Minda Phillips & Pete Brodie, ONS.

Presented by Martin Brand, ONS Methodology Directorate

Outline of Presentation

• The Neighbourhood Statistics Programme– Background– Topics and data sources– Estimating for small areas

• Allsopp Review – Background– Recommendations– Developments

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

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”.

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

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)

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)

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

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

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.

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

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

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

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

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.

Thank you