Measuring Quality Issues Associated with Internal Migration Estimates

1. Demographics Methods Centre and Centre for Demography Measuring Quality Issues Associated with Internal Migration Estimates Joanne Clements, Amir Islam, Ruth Fulton & Jane Naylor

2. Outline • Background • Internal Migration Quality Issues • Research methods • Findings • Issues arising • Next Steps

3. Project • Improve understanding, • measurement and reporting of • the quality of population • estimates

4. Context • Debate about amount of uncertainty in population estimates • Improving Migration and Population Statistics (IMPS) Project – Quality strand • ‘ONS should flag the level of reliability of individual local authority population estimates’ (UK Statistics Authority) • Leading new international research

5. Key Methodology Points • Map out the procedures and data sources used to derive population estimates • Identify associated quality issues • Attempt to quantify uncertainty using statistical theory & empirical evidence instead of expert opinion • Combine individual measures of uncertainty by simulating potential errors in the data

6. Key Methodology Points • Map out the procedures and data sources used to derive population estimates • Identify associated quality issues • Attempt to quantify uncertainty using statistical theory & empirical evidence instead of expert opinion • Combine individual measures of uncertainty by simulating potential errors in the data

7. Key Methodology Points • Map out the procedures and data sources used to derive population estimates • Identify associated quality issues • Attempt to quantify uncertainty using statistical theory & empirical evidence instead of expert opinion • Combine individual measures of uncertainty by simulating potential errors in the data

8. Key Methodology Points • Map out the procedures and data sources used to derive population estimates • Identify associated quality issues • Attempt to quantify uncertainty using statistical theory & empirical evidence instead of expert opinion • Combine individual measures of uncertainty by simulating potential errors in the data

9. Progress • Initial work proved feasibility of simulation methodology • Focus now on sources of error with greatest impact; internal and international migration • Currently focussing on internal migration

10. Internal Migration Methodology • Individual moves captured from GP re-registration data • Annual (end July) download of patient registers • Moves identified from changes with previous year’s download. • Local authority moves constrained to information provided by NHS Central Register

11. Key Internal Migration Quality Issues Not registered at mid-year Time Lags Constraining GP register data to NHSCR data Source LA for out-flows to NI and Scotland Census and 2001 Patient Registers Double counting of School boarders

12. Research Methods • A review of relevant literature. • Local authority level data analysis • Review any internal quality assurance. • Sensitivity analysis

13. Re-registration Time Lag Research • Comparison of mid-2001 internal migration estimates with 2001 Census migration estimates • Sex ratios • Propensity to migrate • Comparison with other data sources • Investigating ‘bumps’ in population age profiles that sustain over time

14. Birmingham Population Age Profile

15. Provisional Time Lag Findings:Sex Ratios • Evidence of late-registration of young male migrants • Geographic variation in sex ratio differences and therefore time lags

16. Provisional Time Lag Findings:Propensity to Migrate • GP List inflation invalidates analysis to compare Census and internal migration propensities • Instead, comparing migrant counts for similar populations to identify possible time lags • Census doesn’t always produce higher LA internal migration estimates

17. Provisional Time Lag Findings:Other Data Sources • Limited other data sources with which to compare with – No major differences with comparator data sources • Evidence from survey data of significant late registration (Median 4 months)

18. Provisional Time Lag Findings:Age Profiles • Some LAs do have age profile bumps that sustain (particularly young adults ages) • Patterns vary again geographically • Possibly due to: • Imbalance between in and out migrants in LAs with higher education institutions (Males especially) • Increases in International immigrants (young males again)

19. Provisional Time Lag Findings:Summary • Evidence of Age-Sex Specific Time lags in re-registration. • Evidence that these vary geographically. • Unclear how much year on year time lags cancel each other out. • Next Step is to produce an potential error distribution

20. School Boarder Research • LAs with largest school boarder populations chosen to identify possible double counting • Comparing age profile changes in school boarders with LA internal migration estimates

21. Provisional School Boarder Findings • Similar patterns between school boarder arrivals and internal in-migration • Therefore, strong evidence of double counting • Difficult to estimate accurately due to data issues • Limited impact, for most LAs, on all age internal migration estimates

22. Challenge: Deriving Error Distributions For Each Quality Issue • Lack of suitable data • Conflicting evidence • Somewhat subjective choice of error bounds • Bias towards larger errors? • Sensitivity Testing • Constraining • Correlation • User Feedback

23. Challenge: Interpretation of Findings • In reality, there is uncertainty in these measures of uncertainty, as… • Only as good as the error assumptions made for each issue • Therefore exact findings are misleading • Present approximate indicators

24. Reporting and Future Work • Short update on progress – August 2009 • Detailed papers on internal migration findings - November 2009 - 2010 • Potential further work: • - international migration • - quantifying impact of methodological changes on quality of estimates