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Developments with ONS’ Small Area Population Estimates Project Andy Bates

Developments with ONS’ Small Area Population Estimates Project Andy Bates. Outline of talk. Current Position Ratio Change method Data Sources used in estimates User Consultation Geography Considerations Future publication and work plans. Current Position Ratio Change method

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Developments with ONS’ Small Area Population Estimates Project Andy Bates

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  1. Developments with ONS’ Small Area Population Estimates ProjectAndy Bates

  2. Outline of talk • Current Position • Ratio Change method • Data Sources used in estimates • User Consultation • Geography Considerations • Future publication and work plans • Current Position • Ratio Change method • Data Sources used in estimates • User Consultation • Geography Considerations • Future publication and work plans

  3. Current Position • Produced mid-2001 and mid-2002 CAS ward estimates • quinary age and sex • Published as experimental statistics • April 2005 • User consultation • 12 weeks • Available on Neighbourhood Statistics this week

  4. Ratio Change method Eg to derive ratios for 0-4 year olds by sex, we create dataset specific ratios: Eg CB ratio = Year 2 dataset count Year 1 dataset count 0-4 ratio = Child Benefit ratio + Patient Register ratio 2

  5. Population 2nd period x ratio SP SP Year 2 Ratio Change method Base population Year 1 Constrain to LA MYEs less SP

  6. Data Sources - Child Benefit • Now provided by Inland Revenue • previously provided by DWP • Receive counts for 0-4’s, 5-9’s & 10-14’s by sex • Data provided for Lower Layer SOAs • Good coverage of children 0-14 • undercount (mid-2003) compared to MYEs 1.7% • Data consistent over time • overall counts • geographically

  7. Data Sources - Older Persons Dataset • Provided by DWP • Comprises a number of benefit databases • eg State Pension, Widows Benefit & Winter Fuel Allowance • Receive counts by quinary age group & sex • 65-69, 70-74, 75-79 & 80+ • Data provided for Lower Layer SOAs • Good coverage of elderly population • undercount (mid-2003) compared to MYEs 1.3% • Data consistent over time & geographically

  8. Data Sources - Patient Registers • Used by ONS to calculate internal migration • Get postcode counts by single year of age & sex • can easily aggregate to different geographies • Issue of list inflation • mid-2004 PR counts > 2004 MYEs by 2.9m (5.4%) • Data not always consistent over time • problems in student areas • problems caused by list cleaning

  9. Data Sources - Patient Registers Patient Register counts less MYEs

  10. Data Sources - Patient Registers 2004 Patient Registers and 2004 MYEs for England & Wales

  11. Data Sources - Patient Registers

  12. User Consultation • 12-week period of consultation • 28 responses received • Govt. depts/agencies2 • Regional Health Observatories1 • Local Government • County Councils 6 • District Councils 3 • Joint Strategy Units & GLA 3 • London Boroughs/Unitaries 13 • 21 organisations completed the response form

  13. User Consultation • Requirement for alternative age groupings • 13-19, 16-19 & 18-19 • Quality of the estimates: • Excellent 1 6% • Good 13 72% • Fair 2 11% • Poor 2 11% • Clear requirement for ward estimates • CAS Wards 3 15% • Standard Table Wards 0 • Statistical Wards 17 85%

  14. User Consultation • Favourable reaction to the estimates • Gives some early indication of Ratio Change suitability However • Base population issue identified in wards with large Armed Forces presence • methodological solution found • Base population distribution - evidence in 2 LAs of ward overestimation and underestimation • further investigation required

  15. Geography Considerations

  16. Geography Considerations – eg Dover, Kent

  17. Geography Considerations – SOAs & Wards Middle Layer SOA Estimates Remove special population MSOA estimates less SPconstrained to Patient Register postcode counts Statistical Wards overlaid onto Patient Register postcodes Patient Register MSOA constrained counts aggregated to Statistical Wards Add back in special population Statistical Ward Estimates

  18. Publication Plans • Mid-2001, mid-2002 & mid-2003 SOA estimates • Lower Layers by broad age group & sex • Middle Layers by quinary age group & sex • publication provisionally planned for early 2006 • Mid-2003 Statistical Ward estimates • only if suitable methodology can be found • problematic because base population may be needed • lack of time series when wards change • if recasting methodology suitable, publish in 2006

  19. Work Plans • Consider methodological enhancements for 3 shortlisted methods • Apportionment • Cohort component • Ratio Change • Evaluate estimates for mid-2002, mid-2003 & mid-2004 from all 3 shortlisted methods • Following evaluation identify a preferred method • Consider transition from Experimental Statistics to National Statistics

  20. Contact Information Email the project team at: SAPE@ons.gov.uk Updated information on the NS website at: www.statistics.gov.uk/SAPE

  21. Any questions?

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