1. Modelling international migration to produce local level estimates Ruth Fulton Office for National Statistics

2. Outline of presentation Context Immigration –Current method –Using administrative data –Modelling approach Data sources, Fitting the model, Diagnostics/ validation, Impact on estimates Emigration

3. Context of work Improving Migration and Population Statistics (IMPS) Previous improvements to immigration and emigration methodology (2007) Forthcoming package of improvements (May 2010)

4. The importance of international migration Key driver of population change

5. Current method: immigration National level –International Passenger Survey (IPS) data only Government Office Region (GOR) & Wales level –IPS data calibrated to Labour Force Survey (LFS) data –LFS data averaged over three years Intermediate geography level –IPS data averaged over three years Local authority level –2001 Census data

6. Current method: issue Current method uses 2001 Census data to distribute to LA level Clear changes in migration trends since 2001 e.g. EU accession Bias introduced to LA estimates where Census distribution has changed

7. Improving the current method:

8. Use of administrative data Potential use of administrative data: GP registrations (Flag 4s) National Insurance Number (NINo) allocations to overseas nationals Improves timeliness at LA level Differences in coverage and definitions

9. Comparison of Flag 4s and NINos

10. A modelling approach Produces estimates for LAs (IPS data cannot be used directly at this level) ‘Borrows strength’ from other data sources (covariates) Model fitted at the LA level describing relationship between IPS and covariates Fitted model can be used to obtain LA estimates

11. Model specification where = direct IPS estimate, no. immigrants going to LADj = expected total count of immigrants, LADj = set of covariates for LADj

12. Alternative approaches Modelling IPS sample counts Modelling IPS sample counts, with average LA weight as offset OR additional covariate Scaling IPS direct estimate to a count scale (or standardising IPS sample count) Fitting model at NMGi level, estimating coefficients and applying model at LA level

13. Choice of covariates Covariates selected which are associated with immigration Direct - counts of actual migrants Indirect - factors associated with migration

14. Variables entered for potential selection NINos Country of Birth Ethnic Population Flag 4s UK-born Immigrants Population Density Foreign Armed Forces Industry Mid-year Pop Est Foreign Students Job Centre Vacancies Home Armed Forces Internal Migration Unemp Estimates

15. Choice of covariates Model fitted for each year to identify most important covariates Fixed set of covariates then selected for use in all models

16. Fixed covariates currently in the model NINoS Country of Birth Ethnic Population Flag 4s UK-born Immigrants Population Density Foreign Armed Forces Industry Mid-year Pop Est Foreign Students Job Centre Vacancies Home Armed Forces Internal Migration Unemp Estimates

17. Diagnostic and Validation tests Model diagnostics Pseudo R 2 Residual plots Model vs Sample estimate plots Comparing the 2001 model based estimates with the 2001 Census data Comparing the sum of the model based estimates for LAs with the NMGi estimate Checking the time-series

18. Time series check

19. Model vs Sample Estimate plot (04/05)

20. 04/05 ExistingNew

21. Preliminary Impacts Assessment 01020203030404050506 ≥ 100066112013 500 to 999181224 20 100 to 4996259554554 -99 to 99181199140108170 -100 to -499968712814999 -500 to -999910122513 ≤ -100043657

22. Current methods: emigration National level International Passenger Survey (IPS) data only Government Office Region (GOR) & Wales level IPS data only Intermediate geography level IPS data averaged over three years Local authority level Model based distribution (propensity to migrate)

23. Improvements Fits model at local authority level rather than intermediate geography level Uses Poisson modelling and models number of migrants rather than propensity to migrate Tested some additional covariates, e.g. more detailed ethnic group and fixes covariates

24. Differences from immigration model Averages IPS data over 3 years Includes an Intermediate geography effect Includes covariates which are associated with emigration Does not include any direct counts of emigrants

25. Impact of model based distribution Only affects the distribution of number of immigrants and emigrants within the intermediate geography Migration estimates for local authorities will change for mid-2002 to mid-2008 as a result

26. Further Information Quarterly updates and other information at www.statistics.gov.uk/imps Email: imps@ons.gsi.gov.uk ruth.fulton@ons.gov.uk Consultation papers (December 09)