Transcript Modelling international migration to produce local level estimates

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
300
Natural change
Net migration & other changes
250
150
100
50
0
2006-2007
2005-2006
2004-2005
2003-2004
2002-2003
2001-2002
2000-2001
1999-2000
1998-1999
1997-1998
1996-1997
1995-1996
1994-1995
1993-1994
1992-1993
-50
1991-1992
Thousands
200
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:
3500
3000
2500
2000
1500
1000
500
0
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
(x=y)
16,000
Birmingham
14,000
12,000
Oxford
Flag 4
10,000
Brent
Nottingham
8,000
Westminster
Sheffield
6,000
Tow er Hamlets
4,000
Canterbury
Hackney
2,000
Herefordshire
0
0
2,000
4,000
6,000
8,000
NINo
10,000
12,000
14,000
16,000
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
Yˆj ~ P(  j )
where
log(  j )    xj β
Yˆ j
= direct IPS estimate, no. immigrants going to LADj
j
= expected total count of immigrants, LADj
xj
= 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
UK-born
Immigrants
Job Centre
Vacancies
Population
Density
Internal
Migration
Unemp
Estimates
NINos
Foreign
Students
Ethnic
Population
Country
of Birth
Mid-year
Pop Est
Industry
Flag 4s
Foreign
Armed
Forces
Home
Armed
Forces
Fixed covariates currently in the model
UK-born
Immigrants
Job Centre
Vacancies
Population
Density
Internal
Migration
Unemp
Estimates
NINoS
Foreign
Students
Ethnic
Population
Country
of Birth
Mid-year
Pop Est
Industry
Flag 4s
Foreign
Armed
Forces
Home
Armed
Forces
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
3000
2500
2000
1500
1000
500
0
2001
2002
2003
West Wiltshire Existing method
2004
Flow(LA)
2005
Flow(NMGi)
2006
Model vs Sample Estimate plot (04/05)
Direct Survey Estimates
25000
20000
15000
10000
5000
0
0
5000
10000
15000
Model Based Estim ates (Unconstrained)
20000
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:
[email protected]
[email protected]
• Consultation papers (December 09)