Monitoring UK internal migration in the twenty-first century

John StillwellCentre for Interaction Data Estimation and Research (CIDER),

School of Geography, University of LeedsPresentation at Workshop on

‘Migration and Labour Markets: China and the UK’, University of St Andrews, 12-14 June, 2010

Acknowledgements

• ESRC Census Programme grant to the Centre for Interaction Data Estimation and Research CIDER (RES-348-25-005)

• Adam Dennett at CIDER for providing some of the slides on migration classification

• ONS for supplying data to CIDER

IntroductionIn recent times, press headlines have been dominated by immigration issues and the call for ‘balanced’ international migration

Importance of internal migration

DestinationsOrigins England Wales Scotland N. Ireland TotalEngland 5,153,436 48,248 43,675 7,899 5,253,258Wales 42,614 243,851 1,546 325 288,336Scotland 42,831 1,396 473,789 2,633 520,649Northern Ireland 8,812 360 2602 127,999 139,773Total 5,247,693 293,855 521,612 138,856 6,202,016

2001 Census records over 6.2 million migrants in the 12 months before the 2001 Census

467,000 immigrants arrived in the same period

406,800 individuals moved but we do not know where from because their origins were unstated

Questions

• What are the key sources of data on internal migration, especially between censuses?

• How has the magnitude, composition and pattern of internal migration changed since 2001

• How do we monitor changing migration trends?

Sources of internal migration data• Census of Population• National Health Service patient re-registrations

from the Central Register in England and Wales (and equivalents in Scotland and Northern Ireland)

• NHS patient registers • Other administrative sources for different migrant

subsets: e.g. HESA for students; School Census for school children; electoral roll for registered electors; ....

• Surveys such as LFS, APS, ..

Census 2001 migrant data

• Comprehensive and reliable• Migrants rather than migrations (i.e. transition data)

but also wholly moving households and moving groups

• Available from ONS at different spatial scales: Districts (426), Wards (10,608), Output Areas (223,060) in the UK

• Special Migration Statistics are tables of origin-destination counts tables by age, sex, ethnicity, family status, economic activity, tenure and NS-SEC

• Adjustments for confidentiality are a particular problem at OA level

NHSCR movement data

• NHS patients re-registering with new doctors are captured by the NHS Central Registers

• Move or event data by age and sex

• Only flows between Health Authorities recorded

• Data for England and Wales obtained by ONS but not joined up with data for Scotland and for N. Ireland

Migration data from patient registers• The Patient Register Data System (PRDS) is a compilation

of all HA patient registers in England and Wales• ONS compare records in one year with those of the

previous year by linking on NHS number enabling identification of each person who changes their postcode

• Transition data (like census) • Patient register data and NHSCR data combined to

produce estimates of population movements for mid-year to mid-year periods for local authority districts in England and Wales by broad age group

• These data now available through the Web-based Interface to Census Interaction Data (WICID)

Web-based Interface to Census Interaction Data (WICID)

WICID allows a user to build a query and extract origin-destination flow data from Censuses in 1981, 1991 and 2001 or from annual (mid-year) patient register/NHSCR flows from 1998-9 onwards

2001 Census

• A lot of analysis based on census data of different aspects of migration

• Aggregate net migration map shows key feature of UK migration pattern in 2000-01

• But 181,476 potential origin-destination flows between 426 districts

Use of district classification system to analyse migration flow data, 2000-01

12 Groups of Vickers et al. classification Top 10 directional migration rates between Groups

Migration since 2001

• How has the magnitude, composition and pattern of internal migration changed since 2001?

• Mid-year population estimates for Local Authority Districts prepared by ONS are very important for resource allocation

• ONS use patient register/NHSCR data as the basis of the internal migration component of the MYEs

• Need to verify relationship between these data and data from the Census if we want to feel comfortable about using the former for monitoring

Verification of NHS data against 2001 Census data for England and Wales

Migration rates are for 376 Local Authority Districts (LADs) in 2000-01

Level of inter-district migration, England and Wales, 1998-99 to 2005-06

Changing patterns of internal migration at district level, England and Wales, all ages

2005-06 Change 2000-01 to 2005-06

Changing patterns of internal migration at district level, England and Wales, ages 16-19

2005-06 Change 2000-01 to 2005-06

Changing patterns of internal migration at district level, England and Wales, ages 60-74

2005-06 Change 2000-01 to 2005-06

Net migration by age for Yorkshire and Humber, 1998-99 to 2006-07

How do we monitor migration over time most effectively?

• The number of potential flows to analyse is quite large: 376 origins x 376 destinations x 8 ages = 1.13million potential flows

• Therefore, what more aggregate systems of spatial units might be appropriate for monitoring

- Counties? - NUTS 2 regions? - Government Office Regions?

• Use a district classification

Net migration changes over time by district type, 1998-99 to 2005-06

Net flows are computed as the sum of net migration balances for districts in each category

District classification based on 2001 Census ‘migration’ variables

• 56 variables were selected from an original list of 5,559 taken from 2001 Census Special Migration Statistics (SMS) level 1 (District) tables

• Domains included:- In/out/within/no usual address migration rates for age, ethnicity, economic activity and long-term illness- Migration efficiencies (due to no suitable denominator) for socio-economic status, family status and housing tenure

• MATLAB used for K-means solution giving 8 clusters

Migration Classification

1 Coastal and rural retirement migrants

2 Sedentary middle-class Britain3 Student towns4 Intermediate single migrants5 Constrained, working class,

local Britain6 Footloose, middle class,

commuter Britain7 Dynamic London8 Successful family in-migrants

Cluster names are provisional

Cluster 1:Coastal and rural retirement migrants

• Characterised by in-migrants and within-area migrants in the older age groups (45 and above)

• Younger in-migrants are very much underrepresented

• Migrants into these areas are from across the socio-economic spectrum, although the very high socio-economic groups are less common

• Migrants preferentially move into owner occupied accommodation and tend to be either or alone or in couples, far more than parent families

Cluster 2:Student towns

• Characterised by high levels of student in-migration, and young person within-area migration

• Non-household moving groups into privately rented accommodation are common in this cluster, as are non-family households and individuals moving into communal establishments – all characteristics of a student population

• In addition, non-white within-area migration is important, as is in-migration of economically inactive migrants

Net migration changes over time by district class, 1998-99 to 2007-08

19992000

20012002

20032004

20052006

20072008

-150000

-100000

-50000

0

50000

100000

Coastal and Rural Retirement MigrantsSedentary Middle-Class BritainStudent TownsIntermediate Single MigrantsConstrained, Working-Class, Local BritainFootloose, Middle-Class, Commuter BritainDynamic LondonSuccessful Family In-migrants

Average in-migration rates, 1999-2008

0-15 16-19 20-24 25-29 30-44 45-59 60-74 75+0

20

40

60

80

100

120

140

160

180Coastal and Rural Retirement Migrants

Constrained, Working-Class, Local Britain

Dynamic London

Footloose, Middle-Class, Commuter Britain

Intermediate Single Migrants

Sedentary Middle-Class Britain

Student Towns

Successful Family In-migrants

Rate

per

1,0

00 p

eopl

e

Age group

Average out-migration rates, 1999-2008

0-15 16-19 20-24 25-29 30-44 45-59 60-74 75+0

20

40

60

80

100

120

140

160 Coastal and Rural Re-tirement MigrantsConstrained, Working-Class, Local BritainDynamic LondonFootloose, Middle-Class, Commuter BritainIntermediate Single MigrantsSedentary Middle-Class BritainStudent TownsSuccessful Family In-migrants

Rate

per

1,0

00 p

eopl

e

Age group

Net migration rates (per 1,000) for clusters, ages 0-15, 1999-2008

-40

-30

-20

-10

0

10

20

1999200020012002200320042005200620072008

Net

mig

ratio

n ra

te p

er 1

,000

Net migration rates (per 1,000) for clusters, ages 16-19, 1999-2008

-80

-60

-40

-20

0

20

40

60

80

100

120

1999200020012002200320042005200620072008

Net

mig

ratio

n ra

te p

er 1

,000

Net migration rates (per 1,000) for clusters, ages 20-24, 1999-2008

-30

-20

-10

0

10

20

30

40

50

1999200020012002200320042005200620072008

Net

mig

ratio

n ra

te p

er 1

,000

Net migration rates (per 1,000) for clusters, ages 25-29, 1999-2008

Coastal and Rural Retirement Migrants

Constrained, Working-Class, Local Britain

Dynamic London

Footloose, Middle-Class, Commuter Britain

Intermediate Single Migrants

Sedentary Middle-Class Britain

Student Towns

Successful Family In-migrants

-25

-20

-15

-10

-5

0

5

10

15

20

1999200020012002200320042005200620072008

Net

mig

ratio

n ra

te p

er 1

,000

Net migration rates (per 1,000) for clusters, ages 30-44, 1999-2008

-40

-30

-20

-10

0

10

20

30

1999200020012002200320042005200620072008

Net

mig

ratio

n ra

te p

er 1

,000

Net migration rates (per 1,000) for clusters, ages 45-59, 1999-2008

Coastal and Rural Retirement Migrants

Constrained, Working-Class, Local Britain

Dynamic London

Footloose, Middle-Class, Commuter Britain

Intermediate Single Migrants

Sedentary Middle-Class Britain

Student Towns

Successful Family In-migrants

-20

-15

-10

-5

0

5

10

15

20

1999200020012002200320042005200620072008N

et m

igra

tion

rate

per

1,0

00

Net migration rates (per 1,000) for clusters, ages 60-74, 1999-2008

-20

-15

-10

-5

0

5

10

15

1999200020012002200320042005200620072008N

et m

igra

tion

rate

per

1,0

00

Net migration rates (per 1,000) for clusters, ages 75+, 1999-2008

-20

-15

-10

-5

0

5

10

1999200020012002200320042005200620072008N

et m

igra

tion

rate

per

1,0

00

Standardised migration ratios (excluding intra-cluster flows), 1998-2008

55 65 75 85 95 105 115 125 135 145 155 165

55

65

75

85

95

105

115

125

135

145

155

165

1999

2008

1999

2008

1999

20082008

1999

2008

2008

Coastal and Rural Retirement Migrants

Dynamic London

Sedentary Middle-Class Britain

Intermediate Single Migrants

Constrained, Working-Class, Local Britain

Successful Family In-migrants

Student Towns

Footloose, Middle-Class, Commuter Britain

In migration

Out

mig

ratio

n

Standardised migration ratios (including intra-cluster flows), 1998-2008

55 65 75 85 95 105 115 125 135 145 155 165

55

65

75

85

95

105

115

125

135

145

155

165

1999

2008 1999

2008

1999

2008

1999

2008

2008

Coastal and Rural Retirement Migrants

Dynamic London

Sedentary Middle-Class Britain

Intermediate Single Migrants

Constrained, Working-Class, Local Britain

Successful Family In-migrants

Student Towns

Footloose, Middle-Class, Commuter Britain

In migration

Out

mig

ratio

n

Conclusions• Internal migration involves around 1 in 10 of population every

year – major determinant of population change• Spatial pattern at district level dominated by metropolitan net

migration gains and non-metropolitan net losses (though patterns vary by age)

• Some fluctuation over time since 2001 in level of migration – likely fall since onset of recession

• Major change in early 2000s was rise and fall in net losses from Greater London

• Bespoke migration classification provides a useful framework for analysing time-series migration patterns

• Clusters exhibit migration profiles with distinctive flow and age characteristics which can fluctuate over time

Some references• Stillwell, J. (2006) Providing access to census-based interaction

data in the UK: that’s WICID, The Journal of Systemics, Cybernetics and Informatics, 4(4): 63-68

• Dennett, A. and Stillwell, J. (2008) Population turnover and churn - enhancing understanding of internal migration in Britain through measures of stability, Population Trends, 134: 24-41

• Dennett, A. and Stillwell, J. (2009) Internal migration in Britain, 2000-01, examined through an area classification framework, Population, Space and Place, Published online May 6 2009. DOI: 10.1002/psp.554

• Stillwell, J., Duke-Williams, O. and Dennett, A. (eds.) (2010) Technologies for Migration and Commuting Analysis: Spatial Interaction Data Applications, IGI Global, Hershey

Thank you

• Working Paper on classification:http://www.geog.leeds.ac.uk/research/wpapers• Details of CIDER available from:

http://cider.census.ac.uk• My contact email:

j.c.h.stillwell@leeds.ac.uk