modelling international migration to produce local level estimates ruth fulton office for national...
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Modelling international migration to produce local level estimates
Ruth Fulton
Office for National Statistics
Outline of presentation
Context
Immigration
– Current method
– Using administrative data
– Modelling approach
Data sources, Fitting the model,
Diagnostics/ validation, Impact on estimates
Emigration
Context of work
• Improving Migration and Population Statistics (IMPS)
• Previous improvements to immigration and emigration methodology (2007)
• Forthcoming package of improvements
(May 2010)
The importance of international migration
• Key driver of population change
UK Components of Change, mid-1991 to mid-2007
-50
0
50
100
150
200
250
300
1991
-199
2
1992
-199
3
1993
-199
4
1994
-199
5
1995
-199
6
1996
-199
7
1997
-199
8
1998
-199
9
1999
-200
0
2000
-200
1
2001
-200
2
2002
-200
3
2003
-200
4
2004
-200
5
2005
-200
6
2006
-200
7
Th
ou
san
ds
Natural change Net migration & other changes
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
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
Improving the current method:
0
500
1000
1500
2000
2500
3000
3500
2001 2002 2003 2004 2005 2006
Peterborough existing Peterborough new method
Fenland existing Fenland new method
Huntingdonshire existing Huntingdonshire new method
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
Comparison of Flag 4s and NINos
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000
NINo
Fla
g 4
Birmingham
Brent
Westminster
Tow er Hamlets
Hackney
Herefordshire
Canterbury
Sheffield
Nottingham
Oxford
(x=y)
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
Model specification
)(~ˆ jj PY
βx jj )log(
where
jY
j
jx
= direct IPS estimate, no. immigrants going to LADj
= expected total count of immigrants, LADj
= set of covariates for LADj
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
Variables entered for potential selection
NINos
Country of Birth
EthnicPopulation
Flag 4sUK-born
ImmigrantsPopulation
Density
Foreign Armed Forces
Industry
Mid-yearPop Est
ForeignStudents
Job CentreVacancies
Home Armed Forces
InternalMigration
UnempEstimates
Fixed covariates currently in the model
NINoS
Country of Birth
EthnicPopulation
Flag 4sUK-born
ImmigrantsPopulation
Density
Foreign Armed Forces
Industry
Mid-yearPop Est
ForeignStudents
Job CentreVacancies
Home Armed Forces
InternalMigration
UnempEstimates
Diagnostic and Validation tests
• Model diagnostics
Pseudo R2
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
Time series check
0
500
1000
1500
2000
2500
3000
2001 2002 2003 2004 2005 2006
West Wiltshire Existing method Flow(LA) Flow(NMGi)
Model vs Sample Estimate plot (04/05)
0
5000
10000
15000
20000
25000
0 5000 10000 15000 20000
Model Based Estimates (Unconstrained)
Dir
ect
Su
rvey
Est
imat
es
04/05
Existing New
Preliminary Impacts Assessment
0102 0203 0304 0405 0506
≥ 1000 6 6 11 20 13
500 to 999 18 12 24 24 20
100 to 499 62 59 55 45 54
-99 to 99 181 199 140 108 170
-100 to -499 96 87 128 149 99
-500 to -999 9 10 12 25 13
≤ -1000 4 3 6 5 7
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)
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
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
Further Information
• Quarterly updates and other information at www.statistics.gov.uk/imps
• Email:
• Consultation papers (December 09)