WP2 workshop, NIESR, November 24-25, 2005

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WP2 workshop, NIESR, November 24-25, 2005

• Volume measures of labour input

2
Reconciling data from different sources

• Which source to use establishment surveys,
  labour force surveys, other (social security
  statistics)
• Issues for discussion
• Options were to impose the same type of source on
  all partners or allow each to decide on the best
  source for their own country?
• In the latter can we adjust data to ensure
  definitions are comparable across countries?

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Reconciling data from different sources UK
example

• Large number of sources Employment Census AES
  (establishment), Annual Business Inquiry ABI
  (establishment), Labour Force Survey LFS
  (individual), Social security data SS
  (individual)
• Data availability
• AES from 1978 LFS from 1984 ABI from
  1998 SS 1970-1978
• All series at least 2 digit SIC some 3 digit
• Sufficient detail to generate full EUKLEMS series

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Comparison LFS (primary jobs) and AES, annual
growth 1996-01 41 industries
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Comparison LFS (primary jobs) and AES, annual
growth 1996-01 20 industries
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Comparison LFS (primary jobs) and AES, ratio
AES/LFS, average 1996-01 41 industries
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Comparison LFS (primary jobs) and AES, ratio
AES/LFS, average 1996-01, 20 industries
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Reconciling data from different sources UK

• Attempt to redefine in terms of common
  definitions
• LFS allocate second jobs to industry where labour
  is employed - Mostly in services

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Reconciling data from different sources
questions

• To what extent have consortium members found
  similar discrepancies between sources?
• Which source should be used?
• As control totals NA if available, but what is
  this?
• To divide by industry small sample sizes
  implies more variation
• LFS coefficient of variation significantly
  negatively correlated with sample size
• Should we combine data sources one as control
  total for broad sectors and use shares of
  sub-sectors in broad sectors from another source
  to disaggregate
• How do we decide what is a small sample

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Industry concordances

• Options for concording
• Optimal get NSI to do it
• Consistent construct weights based on data for
  an overlapping year
• Fudge When data are not available for an
  overlapping year. Use whatever information is
  available to get an approximate concordance
  between industry, then use growth rates in
  another series to construct an overlapping year,
  to ensure no jumps

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Industry concordances

• Consistent construct weights based on data for
  an overlapping year
• Simplest case

Old SIC
New SIC
X
Y Z
X Y Z, so weights are Y/ (YZ) and Z/(YZ)
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Industry concordances

• Consistent Often more complicated

Old SIC
New SIC
X
Y Z
T
W
Set of simultaneous equations but may need
interative procedures if sufficiently
complicated As long as overlapping year data
exist there should not be jumps in the data
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Illustration of fudge method
Time series for industry x
break year
t-1
t
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Industry concordances

• UK example three SICs, 1968, 1980, 1992
• LFS no overlapping year
• AES some overlapping years , e.g. 1990-93 on both
  SIC80 and SIC92, but for detailed (3 digit
  industries) data only available for GB.
• Fudge for LFS could use growth in AES for
  overlapping year to infer an overlapping year in
  LFS. (note levels in AES and LFS differ so cannot
  use AES weights applied to LFS)

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Industry concordances

• Issues for discussion
• To what extent are industry concordances an
  issue?
• What methods have colleagues used to overcome
  problems?
• Can prodsys help?

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Historical data how to fill gaps

• Look for additional data censuses, surveys
• If not available what are the options
• If earlier data are more aggregated then can
  assume growth in sub-industries equal growth in
  aggregate
• If no historical data available then what do we
  do?
• Assume growth rates the same as for aggregate
  economy?
• Assume growth rates the same as other variable in
  EUKLEMS dataset?
• Assume growth rate same as similar industry in
  similar country?

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Data delivery

• Deadline for revised data January 15
• Require prodsys readable form
• Important source of information
• Crucial for productivity calculations
• DOCUMENTATION
• Sources
• Assumptions