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School of Geography FACULTY OF ENVIRONMENT 1 Peter Boden QMSS2 Immigration and Population Dynamics Summer School Projection methods for ethnicity and immigration.

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Presentation on theme: "School of Geography FACULTY OF ENVIRONMENT 1 Peter Boden QMSS2 Immigration and Population Dynamics Summer School Projection methods for ethnicity and immigration."— Presentation transcript:

1 School of Geography FACULTY OF ENVIRONMENT 1 Peter Boden QMSS2 Immigration and Population Dynamics Summer School Projection methods for ethnicity and immigration status 2 – 9 July 2009 International Migration Using administrative datasets for migration analysis and estimation

2 School of Geography FACULTY OF ENVIRONMENT 2 This presentation… 1.European & UK context 2.Data sources 3.Estimation Methods – official statistics 4.New Migrant Databank 5.Estimation Methods – an alternative 6.The impact upon population estimates and projections 7.Adding an ethnic dimension 8.Summary

3 School of Geography FACULTY OF ENVIRONMENT 3 European Context

4 School of Geography FACULTY OF ENVIRONMENT 4 Harmonisation EU Regulation 862/2007 has provided a statutory basis for greater harmonisation of international migration statistics in Europe. Harmonisation remains a long way from being realised (Poulain et al., 2006) and the matrix of inter-country flows is subject to significant issues of coverage and inconsistency between reporting countries (Kupiszewska and Nowok, 2005). THESIM (Towards Harmonised European Statistics on International Migration) MIMOSA (Migration Modelling for Statistical Analysis)

5 School of Geography FACULTY OF ENVIRONMENT 5 UK Research Context

6 School of Geography FACULTY OF ENVIRONMENT 6 UK – Lindsey Oil refinery

7 School of Geography FACULTY OF ENVIRONMENT 7 UK – data quality

8 School of Geography FACULTY OF ENVIRONMENT 8 Migration Statistics Improvement Programme UK Migration Statistics Improvement Programme – New methods – Enhanced data collection – New data – Long-term and short-term migration – Reporting methods

9 School of Geography FACULTY OF ENVIRONMENT 9 Migrant impact Substantial number of studies have supplemented existing statistics (NINO, WRS, LFS) with primary data collection, specifically to examine the ‘impact’ of new migrants upon: – Economy – The workplace – Integration and cohesion – Local service provision Yorkshire & Humber – 120 studies identified Lewis, H. et al (2009) Refugees, asylum seekers and migrants in Yorkshire and Humber, A02620D183A/Refugees_asylum%20seekers%20and%20migrants%20report.pdf A02620D183A/Refugees_asylum%20seekers%20and%20migrants%20report.pdf Some attempts at producing improved migration estimates but generally constrained by sampling difficulties

10 School of Geography FACULTY OF ENVIRONMENT 10 Data Sources

11 School of Geography FACULTY OF ENVIRONMENT 11 Alternative Sources

12 School of Geography FACULTY OF ENVIRONMENT 12 Concepts & definitions Short-term vs long-term migrants Moves vs migrants Census, survey, registers Data captured (workers, students, dependents…) Time-periods

13 School of Geography FACULTY OF ENVIRONMENT 13 Estimation Methods – official statistics

14 School of Geography FACULTY OF ENVIRONMENT 14 National Statistics - UK

15 School of Geography FACULTY OF ENVIRONMENT 15 England & Wales – immigration

16 School of Geography FACULTY OF ENVIRONMENT 16 Estimation process NationalLocalIntermediateRegional

17 School of Geography FACULTY OF ENVIRONMENT 17 New Migrant Databank

18 School of Geography FACULTY OF ENVIRONMENT 18 Objectives of the NMD ‘Single view’ of alternative statistics Understand conceptual and measurement differences Framework for analysis of trends and patterns in migration Analysis of short-term and long-term migration measurement Derivation of ethnic-group migration estimates

19 School of Geography FACULTY OF ENVIRONMENT 19 Datasets

20 School of Geography FACULTY OF ENVIRONMENT 20 Demonstration

21 School of Geography FACULTY OF ENVIRONMENT 21 England – new migrant trends All data are Crown copyright. Sources: 100% data extract from the National Insurance Recording System (NIRS): ONS Mid-year estimates; GP registration statistics provided by ONS England

22 School of Geography FACULTY OF ENVIRONMENT 22 London North West West Midlands Yorks & Humb South West South EastEast North East East MidlandsWales All data are Crown copyright. Sources: 100% data extract from the National Insurance Recording System (NIRS): ONS Mid-year estimates; GP registration statistics provided by ONS England

23 School of Geography FACULTY OF ENVIRONMENT 23 West Midlands and Yorkshire & Humber West MidlandsYorkshire & Humber All data are Crown copyright. Sources: 100% data extract from the National Insurance Recording System (NIRS): ONS Mid-year estimates; GP registration statistics provided by ONS

24 School of Geography FACULTY OF ENVIRONMENT 24 Examples All data are Crown copyright. Sources: 100% data extract from the National Insurance Recording System (NIRS): ONS Mid-year estimates; GP registration statistics provided by ONS Leeds (YH)Bolton (NW)

25 School of Geography FACULTY OF ENVIRONMENT 25 GOR immigration rates: TIM 2006 All GOR excluding London

26 School of Geography FACULTY OF ENVIRONMENT 26 GP Registrations vs TIM estimates Three year comparison

27 School of Geography FACULTY OF ENVIRONMENT 27 Estimation Methods

28 School of Geography FACULTY OF ENVIRONMENT 28 Alternative Models Based on allocation of ‘national’ TIM flows using proportional distribution evident in administrative datasets Do not attempt to use actual counts from administrative datasets Attempt to calculate short-term flows as ‘residual’ of long-term estimation process using administrative datasets.

29 School of Geography FACULTY OF ENVIRONMENT 29 Alternative Models

30 School of Geography FACULTY OF ENVIRONMENT 30 Alternative Models

31 School of Geography FACULTY OF ENVIRONMENT 31 Immigration estimation – Model B IPS – Reason profile, Model B

32 School of Geography FACULTY OF ENVIRONMENT 32 Model Estimation - GOR

33 School of Geography FACULTY OF ENVIRONMENT 33 Model estimation – Yorkshire & Humber

34 School of Geography FACULTY OF ENVIRONMENT 34 Impact upon local population estimates and projections

35 School of Geography FACULTY OF ENVIRONMENT 35 Resource allocation Robust population estimates are a key input to local authority funding, resource allocation and planning plus a wide range of business planning activities. Migration assumptions have been identified as a source of uncertainty for population estimates in a number of local authorities The issue has typically been raised where the immigration estimates are thought to be too low, thus reducing the population estimate Situation is blurred by the difficulty of identifying short-term from long-term migrants Yorkshire & Humber is a region where the immigration estimates may be too high (but there have been no complaints)

36 School of Geography FACULTY OF ENVIRONMENT 36 Population estimates & projections

37 School of Geography FACULTY OF ENVIRONMENT 37 Population Projections – Y&H Yorkshire & Humber Scenario: ‘Revised’ immigration estimates Maintains existing emigration estimates Leaves natural change component unchanged Result Projected regional population in 2026 is reduced by 220K

38 School of Geography FACULTY OF ENVIRONMENT 38 Population Projections – Leeds Leeds Scenario: ‘Revised’ immigration estimates Maintains existing emigration estimates Leaves natural change component unchanged Result Projected regional population in 2026 is reduced by 108K

39 School of Geography FACULTY OF ENVIRONMENT 39 Adding an ethnic dimension

40 School of Geography FACULTY OF ENVIRONMENT 40 NINO Ethnicity 2001 Census – immigration by ethnic group Post 2001 – no other source of data on international migration by ethnic group NINo statistics – immigration by country of origin Leeds Bradford

41 School of Geography FACULTY OF ENVIRONMENT 41 End General information on the project: Link to the paper on immigration estimation:


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