Demographics Methods Centre
and Centre for Demography
Measuring Quality Issues
Associated with Internal
Migration Estimates
Joanne Clements, Amir Islam, Ruth Fulton & Jane
Naylor
1
Outline
• Background
• Internal Migration Quality Issues
• Research methods
• Findings
• Issues arising
• Next Steps
2
Project
Improve understanding,
measurement and reporting of
the quality of population
estimates
3
Context
• Debate about amount of uncertainty in
population estimates
• Improving Migration and Population Statistics
(IMPS) Project – Quality strand
• ‘ONS should flag the level of reliability of
individual local authority population estimates’
(UK Statistics Authority)
• Leading new international research
4
Key Methodology Points
• Map out the procedures and data sources
used to derive population estimates
• Identify associated quality issues
• Attempt to quantify uncertainty using
statistical theory & empirical evidence instead
of expert opinion
• Combine individual measures of uncertainty
by simulating potential errors in the data
5
Key Methodology Points
• Map out the procedures and data sources
used to derive population estimates
• Identify associated quality issues
• Attempt to quantify uncertainty using
statistical theory & empirical evidence instead
of expert opinion
• Combine individual measures of uncertainty
by simulating potential errors in the data
6
Key Methodology Points
• Map out the procedures and data sources
used to derive population estimates
• Identify associated quality issues
• Attempt to quantify uncertainty using
statistical theory & empirical evidence instead
of expert opinion
• Combine individual measures of uncertainty
by simulating potential errors in the data
7
Key Methodology Points
• Map out the procedures and data sources
used to derive population estimates
• Identify associated quality issues
• Attempt to quantify uncertainty using
statistical theory & empirical evidence instead
of expert opinion
• Combine individual measures of uncertainty
by simulating potential errors in the data
8
Progress
• Initial work proved feasibility of simulation
methodology
• Focus now on sources of error with greatest
impact; internal and international migration
• Currently focussing on internal migration
9
Internal Migration Methodology
• Individual moves captured from GP reregistration data
• Annual (end July) download of patient
registers
• Moves identified from changes with previous
year’s download.
• Local authority moves constrained to
information provided by NHS Central Register
10
Key Internal Migration Quality Issues
Time
Lags
Not registered
at mid-year
Source LA for out-flows
to NI and Scotland
Double counting
of School
boarders
Constraining GP
register data
to NHSCR
data
Census and
2001 Patient
Registers 11
Research Methods
•
A review of relevant literature.
•
Local authority level data analysis
•
Review any internal quality assurance.
•
Sensitivity analysis
13
Re-registration Time Lag Research
• Comparison of mid-2001 internal migration
estimates with 2001 Census migration
estimates
• Sex ratios
• Propensity to migrate
• Comparison with other data sources
• Investigating ‘bumps’ in population age
profiles that sustain over time
14
Birmingham Population Age Profile
15
Provisional Time Lag Findings:
Sex Ratios
• Evidence of late-registration of young male
migrants
Source
Census 2001
Internal Migration
00/01
Migrant Sex Ratio
15-29 years
0.915
0.765
• Geographic variation in sex ratio differences
and therefore time lags
16
Provisional Time Lag Findings:
Propensity to Migrate
• GP List inflation invalidates analysis to
compare Census and internal migration
propensities
• Instead, comparing migrant counts for similar
populations to identify possible time lags
• Census doesn’t always produce higher LA
internal migration estimates
17
Provisional Time Lag Findings:
Other Data Sources
• Limited other data sources with which to
compare with – No major differences with
comparator data sources
• Evidence from survey data of significant late
registration (Median 4 months)
18
Provisional Time Lag Findings:
Age Profiles
• Some LAs do have age profile bumps that
sustain (particularly young adults ages)
• Patterns vary again geographically
• Possibly due to:
Imbalance between in and out migrants in LAs with
higher education institutions (Males especially)
Increases in International immigrants (young males
again)
19
Provisional Time Lag Findings:
Summary
• Evidence of Age-Sex Specific Time lags in reregistration.
• Evidence that these vary geographically.
• Unclear how much year on year time lags
cancel each other out.
• Next Step is to produce an potential error
distribution
20
School Boarder Research
• LAs with largest school boarder populations
chosen to identify possible double counting
• Comparing age profile changes in school
boarders with LA internal migration estimates
21
Provisional School Boarder Findings
• Similar patterns between school boarder
arrivals and internal in-migration
• Therefore, strong evidence of double
counting
• Difficult to estimate accurately due to data
issues
• Limited impact, for most LAs, on all age
internal migration estimates
22
Challenge: Deriving Error Distributions
For Each Quality Issue
• Lack of suitable data
• Conflicting evidence
• Somewhat subjective choice of error bounds
- Bias towards larger errors?
- Sensitivity Testing
- Constraining
- Correlation
- User Feedback
23
Challenge: Interpretation of Findings
• In reality, there is uncertainty in these
measures of uncertainty, as…
– Only as good as the error assumptions made for
each issue
• Therefore exact findings are misleading
• Present approximate indicators
24
Reporting and Future Work
• Short update on progress – August 2009
• Detailed papers on internal migration findings
- November 2009
- 2010
• Potential further work:
- international migration
- quantifying impact of methodological
changes on quality of estimates
25