Estimation in the Swedish LFS
–
an example of combining survey
data from independent samples
Martin Axelson & Frida Videll
Statistics Sweden
e-mail: [email protected]
Outline
• The current sampling design for the Swedish LFS
• Combining data from independent samples –
some theory
• Estimation in the Swedish LFS
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The current sampling design for
the Swedish LFS – project 1
• Carried out by Statistics Sweden in 2008
• In response to increased interest in groups outside
or with a weak attachment to the labour market
• Goal: To suggest a cost-efficient way to secure
better statistics for domains of particular interest
• Suggestion: Combine data from two samples
• One drawn according to the design in use
• One drawn according to a design constructed
with high precision for specific parameters and
domains of study in mind.
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The current sampling design for
the Swedish LFS – project 2
•
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•
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• Stratification after
•
•
•
•
•
Region
Sex
Age
Born in Sweden (Y/N)
Not working (Y/N)
• Not working
• Derived using available register information
• Important register: Longitudinal integration database
for health insurance and labour market studies
• Prediction of “Not working” during the reference week
at the individual level
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•
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Combining data from independent
samples – some notation
•
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Combining data from independent
samples – explicit weighting
•
tˆj 

ks j
g j ,k y k
 j ,k
g j ,k  1  ( t x  
ks j
xk
 j ,k
)( 
ks j
x k x
 j ,k
) 1 x k
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Combining data from independent
samples – implicit weighting
•
tˆImp 
J

hk b j ,k yk
j 1 ks j
J
hk  1  ( t x  
j  1 k s j
 j ,k
b j,k x k
 j ,k
J
)( 
j  1 k s j
b j , k x k xk
 j,k
) 1 x k
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Combining data from independent
samples – some relevant facts
•
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Estimation in the Swedish LFS –
project 1
• The possible gains in precision presented by
project 1 were unrealistic
• Numerical results on expected gain based on
(almost) optimal explicit weighting of GREGestimators
• Such weighting amounts to using parameter
specific weight systems, i.e., different weights
are used for different parameters, which NSIs
typically try hard to avoid
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Estimation in the Swedish LFS –
project 2
•
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Estimation in the Swedish LFS –
project 3
•
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Estimation in the Swedish LFS –
today
•
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.
Estimation in the Swedish LFS –
examples of precision gains
•
[Vˆ (tˆLFS ) / Vˆ (tˆO, LFS )]0.5
Expected gain
20
0.91
40
0.85
60
0.79
80
0.75
100
0.71
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.
Estimation in the Swedish LFS –
examples of precision gains
Table 1: Population 20-64 by age and labor status, January 2013
Age
[Vˆ (tˆLFS ) / Vˆ (tˆO ,LFS )]0.5
20-24
25-34
35-44
45-54
55-64
Unemployed Not in the labor force
0.86
0.85
0.83
0.82
0.79
0.81
0.82
0.77
0.76
0.88
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Estimation in the Swedish LFS –
examples of precision gains
Table 2: Population 20-64 not in the labor force by gender, January 2013
[Vˆ (tˆLFS ) / Vˆ (tˆO , LFS )]0.5
Sex
Male
Female
Full-time
students
0.83
0.84
Working
at home
0.72
0.85
Jobseekers, not Retired Long-term Others
available
ill
0.79
0.93
0.80
0.86
0.78
0.91
0.82
0.90
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Estimation in the Swedish LFS –
concluding remarks
•
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Finding solutions to methodological
challenges – reflections from a
methodologist
• Typically requires using (challenging) theory and
methodology
• Theory and practice must go hand in hand – let
implementation be part of the challenge
• Should be seen as an investment, as the short-term
cost is expected to be followed by long-term savings
• Sampling design and estimation are best treated
together, given the strong dependency between
them
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