1. An Improved Method for Estimating Immigration to Local Authorities in England and Wales Nigel Swier British Society of Population Studies (BSPS) Conference York, 7-9 September 2011

2. Overview What is being improved? Issues with producing sub-national immigration estimates Previous approaches Outline of new method How is this new method an improvement? Results (to be released on 17 November)

3. Mid-Year Population Estimates (MYEs): Cohort Component of Change Previous Year Resident Population Add Natural Change (Births – Deaths) Add Net Internal Migration (Inflows – Outflows) “Age On” Add Net International Migration (Immigration – Emigration)

4. Estimating Immigration UN definition of long-term international migrant: “12 months or more” Based mainly on International Passenger Survey (IPS) Adjustments for: -Visitor/migrant ‘switchers’ -Asylum seekers

5. Using IPS to estimate immigration 1.National level IPS estimates are robust 2.Can not produce LA level estimates directly 3.Centralizing tendency

6. Evolution of LA Distribution Methodology Local Authority Immigration Estimates England and Wales Immigration Estimate (IPS) Doesn’t address weaknesses with other parts of the methodology Modelling approach lacks transparency Results are difficult to explain for some LAs Distribute using 3 yr LFS average Use 3 yrs of IPS data Region/ Country Intermediate Geography Uses distributions from admin data not counts. Original concept developed by University of Leeds Enhanced through ONS access to microdata: - Refining definitions - Minimizing double counting Previous (2007) 2001 Census distribution Model-based distribution Current (2010) Distribute using most appropriate admin source Split by Reason for Migration: Work, Study, Returning, Other Improved

7. New Distributional Model Overview Local Authority Immigration (LTIM) estimates GP Patient Register: ‘Flag 4s’ LTM Worker distribution Migrant Workers Scan L2 Residual Asylum Seekers (NASS) Returning Migrants UK Born Non-UK Born Other stream Children 17-59 60+ Student stream Worker stream HESA (Higher Education) BIS/WG (Further Education) STM Student Distribution/ estimate LTM Student distribution IPS England and Wales Estimate (plus switcher adjustments) 2001 Census distribution

8. How is this method an improvement? More transparent Uses more timely data Removes known biases More accurate

9. LA correlations of immigration with APS foreign born (as % of England & Wales total)

10. Next Steps Release on 17 November: - Research paper explaining methods - Indicative immigration (and emigration) estimates - Indicative population estimates - Impact assessment No revisions before 2011 Census results ONS intend to incorporate method into 2010- base SNPPs

11. Questions ?

12. Distributing immigrant IPS flows: workers (first arrivals) Simon Whitworth (ONS) Jennifer Ford-Evans (ONS) Andrew Needham (DWP)

13. Outline Recap of method Use of the International Passenger Survey Use of admin sources Basic methodology Additions to the methodology Summary

14. Who are we distributing? Student flow Worker flow Returning Migrants UK Born Non-UK Born Other flow Children 17-59 60+ Migrant Workers Scan HESA (Public Higher Education) BIS/WAG Data (ESOL/, Further Education) Flag 4: GP Patient Register Asylum Seekers (NASS) L2 Total long and short term migration Residual LTIM LA estimate LTM Worker distribution STM Student Distribution/ estimate LTM Student distribution 2001 Census distribution International Passenger Survey Estimate (plus switcher adjustments)

15. Who are we distributing? All the long-term migrant workers in E&W each year. This total number is taken from the IPS.

16. Identifying LT migrant workers on the IPS Is the country of residence 12 months ago outside the UK? NO Not a Migrant YES

17. Identifying LT migrant workers on the IPS Is the country of residence 12 months ago outside the UK? Is the migrant planning on staying in the UK at least 12 months? NO Not a Migrant Short-term migrant or visitor YES

18. Identifying LT migrant workers on the IPS Is the country of residence 12 months ago outside the UK? Is the migrant planning on staying in the UK at least 12 months? NO Not a Migrant Short-term migrant YES Has the migrant lived in UK before? YES Returning migrant NO

19. Identifying LT migrant workers on the IPS Is the country of residence 12 months ago outside the UK? Is the migrant planning on staying in the UK at least 12 months? Is the migrant aged 16+? NO Not a Migrant Short-term migrant Not a long-term worker YES Has the migrant lived in UK before? YES Returning migrant NO

20. Identifying LT migrant workers on the IPS Is the country of residence 12 months ago outside the UK? Is the migrant planning on staying in the UK at least 12 months? Is the migrant aged 16+? NO Not a Migrant Short-term migrant Not a long-term worker YES Has the migrant lived in UK before? YES Returning migrant NO Is the intended Reason for Visit one of? Definite job to go to Looking for work Working Holiday Business Other but previous occupation not retired or houseperson Accompanying/joining and previous occupation work NO Not a long-term worker YES

21. Identifying LT migrant workers on the IPS Is the country of residence 12 months ago outside the UK? Is the migrant planning on staying in the UK at least 12 months? Is the migrant aged 16+? NO Not a Migrant Short-term migrant Not a long-term worker YES Has the migrant lived in UK before? YES Returning migrant NO Is the intended Reason for Visit one of? Definite job to go to Looking for work Working Holiday Business Other but previous occupation not retired or houseperson Accompanying/joining and previous occupation work NO Not a long-term worker YES LONG-TERM MIGRANT WORKER

22. What we are using to distribute The Lifetime Labour Market Database (L2) and the Migrant Workers Scan (MWS) Derived from the National Insurance and PAYE System (NPS) - a database with records of all National Insurance Number (NINo) registrations since 1975.

23. What the MWS is The MWS is a subset of the NPS and contains information on all the overseas nationals in the NPS It excludes any data about activities Address at registration is used as proxy for address at arrival. It includes both long-term and short-term migrants with no way to distinguish.

24. How is the MWS used in the methodology The MWS is used to get the total count of migrant NINo registrations in an LA.

25. What the L2 is The L2 is a 1% extract of data from the NPS. This 1% contains over 750,000 individuals. The L2 holds detailed records for each tax year from 1975 including activity information. Each record can have various data present.

26. How the L2 is used in the methodology The L2 is used to calculate the proportion of LT migrant workers in an LA.

27. Definitions and assumptions on the L2 Address at registration is used to allocate a geography to a migrant. Activity denotes residency Ceasing activity denotes departure Re-engaging with activity denotes re-arrivals

28. Types of LT migrants

29. Identifying LT migrant workers on the L2 Is the country of origin outside UK and are they coming from abroad? NO Not a Migrant YES (then migrant)

30. Identifying LT migrant workers on the L2 Is the country of origin outside UK and are they coming from abroad? What is the inferred length of stay? Less than 12 months Greater than12 months (then long-term) NO Not a Migrant Short-term migrant YES (then migrant)

31. Identifying LT migrant workers on the L2 YES What is the inferred length of stay? Less than 12 months Greater than12 months (then long-term) NO Not a Migrant Short-term migrant YES (then migrant) Does the LT migrant have an employment/self-employment record, JSA record or Working Tax Credit? Not a long-term worker Is the country of origin outside UK and are they coming from abroad?

32. Identifying LT migrant workers on the L2 YES What is the inferred length of stay? Less than 12 months Greater than12 months (then long-term) NO Not a Migrant Short-term migrant Not a long-term worker YES (then migrant) Does the LT migrant have an employment/self-employment record, JSA record or Working Tax Credit? Are there 6 months or less between arrival and registration? YES Not a long-term worker Is the country of origin outside UK and are they coming from abroad?

33. Identifying LT migrant workers on the L2 YES What is the inferred length of stay? Less than 12 months Greater than12 months (then long-term) NO Not a Migrant Short-term migrant Not a long-term worker YES (then migrant) Does the LT migrant have an employment/self-employment record, JSA record or Working Tax Credit? Are there 6 months or less between arrival and registration? YES Not a long-term worker Is the LT migrant worker a “potential student”? YES LT worker who is also a student (Taken out to eliminate duplication between streams) NO Is the country of origin outside UK and are they coming from abroad?

34. Identifying LT migrant workers on the L2 YES What is the inferred length of stay? Less than 12 months Greater than12 months (then long-term) NO Not a Migrant Short-term migrant Not a long-term worker YES (then migrant) Does the LT migrant have an employment/self-employment record, JSA record or Working Tax Credit? Are there 6 months or less between arrival and registration? YES Not a long-term worker Is the LT migrant worker a “potential student”? LONG-TERM MIGRANT WORKER YES LT worker who is also a student (Taken out to eliminate duplication between streams) NO Is the country of origin outside UK and are they coming from abroad?

35. Recap of methodology LT worker figure for LA “X” = MWS count in LA “X” x L2 proportion of LT workers in LA “X”

36. Recap of methodology Student flow Worker flow Returning Migrants UK Born Non-UK Born Other flow Children 17-59 60+ Migrant Workers Scan HESA (Public Higher Education) BIS/WAG Data (ESOL/, Further Education) Flag 4: GP Patient Register Asylum Seekers (NASS) L2 Total long and short term migration Residual LTIM LA estimate LTM Worker distribution STM Student Distribution/ estimate LTM Student distribution 2001 Census distribution International Passenger Survey Estimate (plus switcher adjustments)

37. Sample size issues Using the method just described, the 1% L2 sample size means that in some LAs, the proportion of workers is very variable over time. In these cases, the proportion could not be used directly at LA level.

38. Sample size issues To compensate for this, we have applied the proportion of LT workers at a higher geography to those LAs that were deemed not sufficiently robust. The proportion is applied to the MWS oDirectly at LA level in the case of 59 LAs. oAt NUTS 3 geography in the case of 203 LAs. oAt NUTS 2 geography in the case of 114 LAs.

39. Sample size issues NUTS 2 in East of England: East Anglia Essex Bedfordshire and Hertfordshire NUTS 3 in East of England East Anglia Cambridgeshire Peterborough Norfolk Suffolk Essex Essex CC Thurrock Southend-on-sea Bedfordshire and Hertfordshire Luton Bedfordshire CC Hertfordshire

40. Sample size issues In the East of England, there are: 2 LAs which use the proportion at NUTS 2 level 42 which use the proportion of LT workers at NUTS 3 level 4 which use the proportion of LT workers directly at LA level

41. Reconciling IPS and L2 The two groups of LT migrant workers (IPS and L2) were compared Some differences in the country of origin breakdowns were discovered

42. Reconciling IPS and L2 Accounting for this, a “subcontinent weighting factor” was introduced based on the E&W subcontinent split. EUAsiaRoWAus/NZ EU Asia RoW Aus /NZ L2 IPS LT workers

43. Summary of methodology Calculate LT worker proportion in the L2 and apply to MWS count

44. Summary of methodology LT worker figure in each LA from L2 and MWS Calculate LT worker proportion in the L2 and apply to MWS count

45. Summary of methodology Calculate LT worker proportion in the L2 and apply to MWS count Split into subcontinents LT worker figure in each LA from L2 and MWS EU Asia RoW Aus /NZ

46. Summary of methodology Calculate LT worker proportion in the L2 and apply to MWS count Split into subcontinents Calculate weighting factor from IPS subcontinent split and weight L2 based data LT worker figure in each LA from L2 and MWS EU Asia RoW Aus /NZ L2/MWS E&W Before

47. Summary of methodology Calculate LT worker proportion in the L2 and apply to MWS count Split into subcontinents Calculate weighting factor from IPS subcontinent split and weight L2 based data LT worker figure in each LA from L2 and MWS L2/MWS E&W After EUAsiaRoWAus/NZ

48. Summary of methodology Calculate LT worker proportion in the L2 and apply to MWS count Split into subcontinents Calculate weighting factor from IPS subcontinent split and weight L2 based data Distribute each IPS subcontinent total using weighted L2/MWS distributions and sum together to get total LT worker counts by LA LT worker figure in each LA from L2 and MWS EU Asia RoW Aus /NZ EUAsiaRoWAus/NZ LT workers in each LA that sum to IPS E&W total

49. Any questions? ?

50. Using administrative data to distribute long-term international immigrant students to Local Authority (first arrivals) Helena Howarth and Sofie De Broe BSPS Conference (York): 7-9 September 2011

51. Overview of Presentation 1.Defining students in the IPS 2.Defining the student subgroups a.Group 1 – Higher Education Students at Government Funded Institutions a.Group 2 – Higher Education Students at Privately Funded Institutions a.Group 3 – Further Education Students 3.Distributing students to Local Authority Level

52. New Distributional Model Overview Student flow Worker flow Returning Migrants UK Born Non-UK Born Other flow Children 17-59 60+ Migrant Worker Scan HESA (Higher Education) BIS/WG (Further Education) Flag 4: GP Patient Register Asylum Seekers (NASS) L2 Total long and short term migration STM Worker Distribution/ estimate LTIM LA estimate LTM Worker distribution STM Student Distribution/ estimate LTM Student distribution 2001 Census distribution International Passenger Survey Estimate (plus switcher adjustments)

53. Relative sizes of groups Estimates for mid-2006 to mid-2010 show that students have become the largest group.

54. Identifying LT migrant students on the IPS Is the country of residence 12 months ago outside the UK? Is the migrant planning on staying in the UK at least 12 months? Is the migrant aged 17-59? NO Not a Migrant Short-term migrant Not a long- term student YES Has the migrant lived in the UK before? YES Returning migrant NO Is the intended Reason for Visit ‘Formal Study’ NO Not a long- term student YES LONG-TERM MIGRANT STUDENT YES

55. Student groups 1.“Higher education (HE) students are those students on programmes of study for which the level of instruction is above that of level 3 of the National Qualifications Framework” (HESA) Proportions HE/FE from 2004 and 2005 IPS data 2.HE publicly-funded versus HE private or for-profit institutions Proportions from a Home Office publication on Visa compliance and comparing counts in the HESA student record versus IPS estimates.

56. Reason for distributing HE and FE separately 5 Welsh LA’s: 6 FE institutions 5 HE institutions 0 private institutions

57. HE Government - Processing (1) Sub-setting HESA data (2) Linking to other administrative sources (3) Imputation of missing term-time addresses

58. HE Government – Sub-setting Group RemovedReason Domicile = UKNot migrants Year >= 2Not in their first year of study therefore a different migrant inflow Campus = AbroadThey have not migrated to the UK Previous institution in UK Not their first UK institution therefore a different migrant inflow or in ‘returning migrant’ stream Start date to End date < 365 days Short-term migrant Age =60Children and older people are distributed separately as part of the ‘other’ stream Mode = Distance learning Assumed that individuals would not migrate to distance learn

59. HE Government - Linkage HESA Student Record – Current Year Migrant Workers Scan – Quarterly data to present HESA Student Record – Previous Year Linked using: 1)Student Identifier 2)3 letters of forename, 3 letters of surname, sex and date of birth Linked using: 1)Date of birth, sex and term-time postcode 2)Repeat for all available postcodes

60. HE Government - Imputation Term-time address is sometimes missing. HESA is actively working with universities to decrease the proportion missing. Migrant subset in:2007/08 ~ 22% missing 2009/10 ~ 13% missing The percentage missing varies by institution Method of imputation: Find LA level distribution of students with term-time address by campus Apply this distribution to those with no term-time address by campus

61. HE Private HESA conducted a census of Private Providers of HE education in 2010. This asked for aggregate data by: 1) mode of study 2) level of study 3) domicile 4) subject Institution address used to allocate students: oOutside London – Term-time address distribution of HESA government institutions in the LA where available and LA of institution where not. oLondon – Term-time address distribution of all HESA government institutions in the London region

62. Further Education Datasets: Individualised Learner Record (BIS) Lifelong Learning Wales Record (Welsh Government) Key Points: Domicile known Term-time address No length of stay data Coverage based on funding

63. Combining the Data – Region Note – The figures used in this example are as closely allied to the data we have used as available from published sources but do not represent our final results.

64. Combining the data - Method Take the proportions of all students in each group: HE Government = 0.68 HE Private = 0.12 FE = 0.20 Apply these proportions to the distributions produced for each region: e.g. London HE Government = 27.7% HE private = 60.5% FE = 12.4% 0.68*27.7 + 0.12*60.5 + 0.20*12.4 = 28.6% Apply this proportion to the total number of migrant students: e.g. London in 2009/10 0.286*195k = 56k

65. Combining the data - Result

66. Any Questions?