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
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Outline of presentation
Context
Immigration
– Current method
– Using administrative data
– Modelling approach
Data sources, Fitting the model,
Diagnostics/ validation, Impact on estimates
Emigration
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Context of work
• Improving Migration and Population Statistics (IMPS)
• Previous improvements to immigration and emigration methodology (2007)
• Forthcoming package of improvements
(May 2010)
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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
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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
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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
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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
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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
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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)
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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
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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
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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
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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
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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
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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
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Time series check
0
500
1000
1500
2000
2500
3000
2001 2002 2003 2004 2005 2006
West Wiltshire Existing method Flow(LA) Flow(NMGi)
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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
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04/05
Existing New
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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
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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)
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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
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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
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Further Information
• Quarterly updates and other information at www.statistics.gov.uk/imps
• Email:
• Consultation papers (December 09)