1

Combining migration data from multiple sources: Applications to internal movements in England, 1999-2007James Raymer

with Peter W.F. Smith and Corrado GiuliettiSouthampton Statistical Sciences Research Insitute (S3RI)

Centre for Spatial Analysis and Policy, University of Leeds, 19 February 2009

ESRC project on Combining Migration Data in England and Wales

• Develop a methodology for combining migration data and for producing ‘more detailed’ flows over time

• Applications include flows by ethnicity, economic activity and education at regional, county and area group levels

Background

• Internal migration data in England are limited due to differences in sources, availability, quality and measurement, e.g., – National Health Service Central Register– Census– Labour Force Survey

Significance

• The combination of multiple data sources increases the capacity to study migration and population change for specific groups by producing – harmonised data sets– time series

• Estimates can be used for subnational projections, planning or policies

Outline

• A general log-linear model for combining data

• Ethnic migration at regional level, 1991-2007– Combining census and health registration data– Results

• Economic activity migration at county level, 1999-2007– Combining census, survey and health registration

data– Results

• Conclusions and future work

A general log-linear model for combining migration data

• We are interested in estimating five-way migration flow tables over time

• The five dimensions are origin, destination, age, sex and some other ‘more detailed’ variable

• Migration flow tables are composed of various hierarchical structures, not all of which are necessary for accurate prediction

• If certain (important) structures are unavailable, they can be ‘borrowed’ from auxiliary data sources

Log-linear models for origin, destination and age migration flow tables• Saturated model

• Unsaturated model

• Unsaturated-with-offset model

ODij

Ax

Dj

Oi

ODAijx log

)log(log ODAijx

ODij

Dj

Oi

ODAijx m

ODAijx

DAjx

OAix

ODij

Ax

Dj

Oi

ODAijx log

Ethnic migration • Categorical variables– 9 origins (O) and

destinations (D)– 16 age groups (A) – 2 sexes (S)– 4 ethnic groups (E)

• 1991-2007 National Health Service (NHS) register*– OD, OAS and DAS

tables each year

• 1991 and 2001 censuses– ODAS and ODSE

* Males undercounted

Reported proportions of NHS interregional migration in England by sex, 1991-2007

1991 and 2001 Census = 50.8 M and 49.2 F

0.46

0.48

0.50

0.52

0.5419

91

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Prop

orti

on

Male Female

Age patterns of NHS interregional migration in England by sex, 1991 and 2007

0

20

40

60

80

100

120

0-4

5-9

10-1

4

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75+

Tho

usan

ds

Age Group

M 1991 F 1991 M 2007 F 2007

Adjustment ratios for NHS migration data Both

Year 15-19 20-24 25-29 Males Sexes1991 1.315 1.436 1.131 1.123 1.0591992 1.287 1.411 1.128 1.117 1.0561993 1.300 1.409 1.131 1.120 1.0581994 1.294 1.398 1.136 1.116 1.0561995 1.322 1.385 1.121 1.117 1.0561996 1.334 1.403 1.130 1.122 1.0581997 1.339 1.408 1.136 1.119 1.0571998 1.348 1.441 1.156 1.125 1.0591999 1.344 1.433 1.157 1.122 1.0582000 1.343 1.454 1.176 1.127 1.0602001 1.388 1.473 1.161 1.131 1.0622002 1.393 1.482 1.177 1.130 1.0622003 1.399 1.487 1.188 1.132 1.0632004 1.400 1.514 1.217 1.137 1.0652005 1.390 1.490 1.223 1.138 1.0662006 1.399 1.523 1.255 1.145 1.0692007 1.400 1.553 1.281 1.148 1.070

Age Group

Basic framework

• Data preparation

• Identification of key structures and theoretical model

• Estimate the flows

• Analyse the results

Identifying the ethnic migration model: Analysis of Census 2001 data structures• ODAS table

– Key structures are OD, OA, DA and AS

• ODSE table

– Key structures are ODE, S

• Theoretical model (ODASE)

– ODE, OA, DA, AS

Model specification

ODEijz

ASxy

DAjx

OAix

ODij

ODASEijxyz mloglog

Steps• Construct time series of ODE tables

using geometric interpolation of counts from 1992 to 2000 and extrapolation to 2007

• Use iterative proportional fitting to estimate flows, where the ODE tables are adjusted to match simultaneously all of the counts imposed by the NHSCR tables

• Adjust counts of males for three age groups

NHSCR Census

0

10

20

30

40

50

60

70

80

1991 1993 1995 1997 1999 2001 2003 2005 2007

Tho

usan

ds

South Asian Black Chinese & Other

Results: Estimated levels of South Asian, Black and Chinese & Other interregional migration in England, 1991-2007

% White1991 = 942001 = 902007 = 85

0

1

2

3

4

5

6

7

8

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

ds

0

1

2

3

4

5

6

7

8

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

ds

0

1

2

3

4

5

6

7

8

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

ds

0

10

20

30

40

50

60

70

80

90

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

dsResults: Estimated interregional migration from London by ethnicity, 1991-2007

White South Asian

Black Chinese & Other

DestinationsNE NWYH EMWM EASE SWLO

SE

EA

SW

SE

EA

WM

SE

EA

EASE

WM

0

10

20

30

40

50

60

70

80

90

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

ds

0

1

2

3

4

5

6

7

8

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

ds

0

1

2

3

4

5

6

7

8

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

ds

0

1

2

3

4

5

6

7

8

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tho

usan

ds

Results: Estimated interregional migration from South East by ethnicity, 1991-2007

White South Asian

Black Chinese & Other

DestinationsNE NWYH EMWM EASE SWLO

LO

SW

EA

LO

LO

LO

0

100

200

300

400

500

600

700

800

900

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75+

Age

1991 1999 2007

0

100

200

300

400

500

600

700

800

900

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75+

Age

1991 1999 2007

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75+

Age

1991 1999 2007

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75+

Age

1991 1999 2007

Results: Estimated age-specific migration of female South Asians: 1991, 1999 and 2007

West Midlands to London

London to South East

South East to London

London to West Midlands

• Categorical variables– 47 origins (O) and

destinations (D)– 12 age groups, 15-74

(A)– 2 sexes (S)– 6 economic activity

groups (G): Self employed, employee, unemployed, retired, other inactive and students

• 1999-2007 NHS Patient Registry Data System*

– OD, OAS and DAS tables each year

• 2001 census– ODAS and ODSG

• 1999-2007 Labour Force Survey

– AG and SG

Economic activity migration

* Males undercounted

Age patterns of PRDS inter-county migration in England by sex, 1999 and 2007

0

20

40

60

80

100

120

140

160

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

Tho

usan

ds

Age Group

M 1999 F 1999 M 2007 F 2007

Identifying the economic activity migration model

• Theoretical model (ODASG)

– ODG, OA, DA, AS, AG, SG

• 1st step: Combine LFS and Census data

• 2nd step: Combine estimates from 1st step with PRDS data

ODASGijxyz

ASxy

DAjx

OAix

ODij

ODASGijxyz mloglog

ODGijz

SGyz

AGxz

ODASGijxyz mm loglog

-

200

400

600

800

1,000

1,200

1,400

1999 2001 2003 2005 2007

Tho

usan

ds

Employee Student Inactive Retired Self-Employed Unemployed

Results: Overall levels of migration by economic activity groups, 1999-2007

20% of all outflows15% of all outflows10% of all outflows5% of all outflows2% of all outflows

67% of all outflows

20% of all outflows15% of all outflows10% of all outflows5% of all outflows2% of all outflows

66% of all outflows

Results: Spatial patterns of employee and inactive migration from Greater Manchester (top 10 flows), 1999

Employee Inactive

20% of all outflows15% of all outflows10% of all outflows5% of all outflows2% of all outflows

71% of all outflows

Results: Spatial patterns of student migration from Greater Manchester and Hampshire (top 10 flows), 1999

20% of all outflows15% of all outflows10% of all outflows5% of all outflows2% of all outflows

65% of all outflows

20% of all outflows15% of all outflows10% of all outflows5% of all outflows2% of all outflows

69% of all outflows

Results: Spatial patterns of retired migration from Greater Manchester and Hampshire (top 10 flows), 1999

20% of all outflows15% of all outflows10% of all outflows5% of all outflows2% of all outflows

70% of all outflows

Lancashire Merseyside CheshireWest Yorkshire Devon

0

200

400

600

1999

2000

2001

2002

2003

2004

2005

2006

2007

0

500

1000

1500

2000

1999

2000

2001

2002

2003

2004

2005

2006

2007

Results: Spatial patterns of retired migration from Greater Manchester (top 5 flows), 1999-2007

Results: Age- and sex-specific migration of selected economic activity groups from Greater Manchester (top flow), 1999

0

100

200

300

400

500

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

Male Female

0

100

200

300

400

500

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

Male Female

0

100

200

300

400

500

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

Male Female

0

100

200

300

400

500

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

Male Female

Employee to Cheshire Retired to Lancashire

Students to West YorkshireInactive to Lancashire

Conclusions

• Flexible model and framework for combining migration data– Level of detail– Geography– Sources of information

• Result is a synthetic data base that takes advantage of several available data sources

• Estimates can be used for analysis, projections or planning

Future work

• In the next six months– Model ethnic migration flows at county level – Extend approach to estimate flows by education– Test model to predict flows between local

authorities, say, within a county or region

• In the next few years…– Link this framework and resulting estimates

with subnational population modelling– Extend this framework to analyse other

transition data, such as health, labour force and household change

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Contact information

James Raymer

Southampton Statistical Sciences Research Institute (S3RI)University of SouthamptonSouthampton SO17 1BJ

Email: raymer@soton.ac.uk

See also Raymer J, Smith PWF and Giulietti C (2008) Combining census and registration data to analyse ethnic migration patterns in England from 1991 to 2007. University of Southampton Statistical Sciences Institute Methodological Working Paper, M08/09. Available at: http://eprints.soton.ac.uk/63739/01/s3ri-workingpaper-M08-09.pdf