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Alison Pritchard
ONS, UK
ESSnet Admin Data
Introduction
• ESSnet Admin Data ran for 4 years (2009–2013);
• Partnership of 8 NSIs – BE, DE, EE, IT, LT, NL,
PT and UK;
• Very ambitious work programme, divided
between 8 workpackages;
• True partnership, with at least 3 co-partner NSIs
involved in each work package.
• Collaboration - when it works, it’s both satisfying
and interesting!
Aims of ESSnet Admin Data
To recommend best practices for dealing with the
following identified problems:
• Poor timeliness of admin data for STS (WP4);
• SBS definitions differ from those used in
admin and accounts data (WP7);
• Some variables are not available at all in
admin sources (WP3);
• No quality measures (WP6);
• Errors in admin data (WP2).
SBS v. IFRS definitions
• Aim of WP7 - to determine how useful accounts
data are, as replacements for SBS survey data.
• Definitions in International Accounting Standards
were compared with SBS, building on the results
in ICON Institute’s Taxonomy Report.
• Actual accounts were compared with SBS survey
- do the definitional differences matter in practice?
• If they do, WP3 team members then endeavoured
to estimate the variables in other ways using
admin data.
SBS Turnover v. IAS/IFRS Revenue
Excise Duties:
• IFRS Revenue includes only the gross inflows of
economic benefits;
• Amounts collected on behalf of third parties are
not economic benefits;
• Therefore, Revenue generally excludes excise
duties (except, theoretically, in very rare cases);
• SBS Turnover includes all duties and taxes on
goods and services invoiced by the unit, except
for VAT, unlike the requirements of IAS/IFRS.
WP7’s Conclusions re Turnover/Revenue
• Recommendation to exclude Excise Duties from
SBS Turnover definition, so that company
accounts can be used directly.
• Impact of the other definitional differences – re
grants, interest, royalties and dividends - was
shown to be insignificant for SBS results.
Purchases
• SBS variable Total purchases of goods and
services does not exist in Financial Statements,
but calculation is possible where nature of
expenses method is used, because definitional
differences are not significant for SBS results.
• Where function of expenses method is used,
must also extract information from the Notes.
Production value - SBS v. IAS/IFRS
SBS IAS/IFRS
Turnover (12110)
Revenue
+/- Change in stocks of finished
products and work in progress
(13213)
Is recorded in the Income Statement
based on the nature of expense method
or
+/- Change in stocks of goods and
services purchased for resale
(13211)
calculated from the classified inventories
which are disclosed either in the Balance
sheet or in the Notes.
- Purchases of goods and services
purchased for resale (13120)
The calculation of the variable is
complicated and basically impossible.
Personnel costs v. Employee benefits
SBS defines Personnel costs as:
Total remuneration, in cash or in kind, payable by employer
to employee in return for work done during the reference
period.
Personnel costs are made up of Wages and salaries and
Social security costs, including taxes and employer's
compulsory and voluntary social contributions.
IFRS splits Employee benefits into 4 categories:
1. short-term employee benefits, such as wages, salaries
and social security contributions;
2. post-employment benefits, such as pensions;
3. other long-term employee benefits, including long-
service leave, sabbatical leave etc.; and
4. termination benefits.
Accounting data v. Social Security data
Total labour cost in the annual profit & loss account tends to be higher than in admin source.
Possible reasons: • Inclusion of certain overhead costs;
cost of compliance with labour legislation
outsourcing salary administration/ executive search...
• Foreign staff on the payroll;
• Tax avoidance (especially for highest paid employees).
Conclusions from further analysis of the metadata: • content of social security office’s records is subject to
modification, resulting from legislative changes;
• Failure to comply biased personnel cost estimates.
Investment variables
• Values for total fixed assets at end (and start) of
year are available in Balance sheets;
• Acquisitions, disposals, transfers and value
adjustments of fixed assets may be in the Notes.
• Acquisitions are measured at fair value rather than
cost, but in practice this difference is not
significant.
• Detailed data about the nature of the fixed asset
invested in (land/buildings/improvements/plant)
are usually not available.
Sales of fixed assets
• Analysing company accounts is very time-
consuming, in the absence of xbrl data;
• The disposal value of a fixed asset is not the
same as the amount deducted in the balance
sheet, because accounts use book value, not
sale proceeds;
• But the sales proceeds of investment goods may
be found in the Cash Flow Statement.
WP7’s recommendations
• Revenue can be used for SBS variable Turnover,
as discrepancies arising from differences between
IAS/IFRS and SBS requirements are small (this
excludes the impact of excise duty which needs to
be measured individually).
• The definition of Turnover should be amended to
exclude excise duties;
• The data from the Notes to the Financial
Statements should be made available to EU NSIs
in a useable format (e.g. the IFRS xbrl Taxonomy
is a likely source).
Estimating difficult SBS variables (WP3)
• Change in stocks
• Purchases
• Payments for agency workers
• FTE
• Gross investment (and components) and Sales of tangible investment goods
• Production value (derived variable)
Investment: UK – Cut-off sampling
• Unit level regression modelling produces
largest sample size savings:
• GITG model fitted using sample data from cut-off
band in last year survey was run – model
parameters fixed over time
• STIG model fitted using sample data from above
the cut-off band – model parameters can be
updated annually
• Simple ratio adjustment method works well too;
• Sample size saving depends on size of
divisions where method works well.
WP3 Scenario Estimation methods to try
Admin variables are available with
strong correlation with SBS variable
Regression modelling for
whole population
Multiple admin variables are
available with reasonable correlation
with SBS variable
Cut-off sampling with:
Simple ratio adjustment;
or Regression modelling
Single available admin variable has
reasonable correlation with SBS
variable
Cut-off sampling with
simple ratio adjustment
To make a saving on an existing ratio
estimation survey approach. Inflation of survey weights
Estimating for Components
• Admin variables are available for the total, but
not for components.
• Work done on components of total gross
investment in tangible goods (Lithuania).
• Work done on components of change in stocks
(Italy).
• Recommend using admin data for totals, and
survey questionnaires (sent only to largest
enterprises) for components; then can estimate
components for smaller enterprises.
Derived variable – production value (UK)
• Production value = turnover - purchases for resale
+ change in stocks + capitalised production + other
income.
• Three admin sources available in UK:
• Social security employment;
• VAT turnover and expenditure; and
• Company accounts
• Investigated use of cut-off sampling for:
• Estimating Production Value total; and
• Estimating the components and then combining them to
give the Production Value total
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Results – estimating components
• Simple ratio adjustment method applied to each
component
• Number of divisions with acceptable results:
• Harder to estimate for some of the components,
very small estimates & lots of zeroes.
Ratio Auxiliary variable
Production
value Turnover Purchases
Change in
stocks
Capitalised
production
Other
income
Overall Register turnover 32 33 1 3 7 8
Overall
Register
employment 31 25 3 3 8 10
Division Register turnover 31 33 13 3 9 14
Division
Register
employment 30 30 10 3 9 15
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WP3 Scenario Estimation methods to try
Admin data are
available for the total,
but have to estimate
components for some
businesses
Estimate breakdown from similar
businesses and apply to total, using - Nearest neighbour donor imputation; or Cut-off sampling with simple ratio
adjustment
To estimate a total and
related components for
some businesses
Nearest neighbour donor imputation; or Cut-off sampling with simple ratio
adjustment.
To estimate a derived
variable
Estimate directly; or Retain some components in survey and
estimate the rest separately.
Top 25 IC user countries, in the last year
• 20 May 2012 to 19 May 2013
• 4,427 visits from 95 countries
Sequence Country Visits
1. United Kingdom 846
2. Italy 720
3. Belgium 259
4. Estonia 250
5. Netherlands 233
6. Poland 142
7. Germany 131
8. Lithuania 122
9. Bulgaria 112
10. Austria 109
11. Finland 108
12. New Zealand 104
13. Cyprus 88
14. Hungary 84
15. Switzerland 80
16. Sweden 67
17. Slovakia 61
18. Spain 55
19. Romania 55
20. Latvia 52
21. United States 52
22. Croatia 48
23. Turkey 47
24. Slovenia 46
25. Luxembourg 39
Information Centre - essnet.admindata.eu
Advanced search options - can search within work
package articles, documents, events, reference
library articles, glossary items etc.
Project-wide Glossary – defines various terms
related to the use of administrative data and
accounts data (Wiki functionality).
Database of existing practices - user-friendly
application database with up-to-date data and user
interface (for online queries).
Reference library - repository of reference literature
(about 600 items).
Thank you…any questions?
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