Results and next steps from the
ESSnet Admin Data
Alison Pritchard
Business Outputs & Developments,
Office for National Statistics, UK
4 December 2012
Introductory and general remarks
• Part of MEETS Programme
• Focus is mainly on the statistical outputs
required by the STS and SBS Regulations;
• There are 8 participating NSIs – UK, NL, LT, IT,
EE, DE and BE;
• The agreed work programme is very ambitious,
so it’s been divided between 8 workpackages;
• This presentation covers progress made during
the first 3 years and future plans.
Aims of the ESSnet Admin Data
“The use of administrative and accounts data for
business statistics has country specific problems
as well as problems common for most of the MSs.
The common problems concern the methods of
quality checking, editing and estimation of
missing variables. One of the ways to help NSIs
solve common problems is to create an ESSnet
where several MSs interested in the topic can
collaborate on the common task, and then
disseminate the results to non-participating
members.”
Overview of existing practices in MSs
The areas covered are: SBS, STS, Prodcom and
Business Registers (only because these are used as
the sampling frame for business statistics).
• Collection of all relevant literature in one place;
• Searchable database of literature and current
practices of European NSIs;
• Glossary of terms relevant to the use of
administrative data for business statistics;
• All the results of the 2010 review have been
published on this ESSnet’s Information Centre
(essnet.admindata.eu).
Overview of existing practices in MSs
Want the searchable online database to provide upto-date information.
• Expanding glossary a little now, working with
MEMOBUST colleagues;
• Already updated literature repository;
• Minimum burden on MSs because just asking
them to tell us about developments since 2010;
• Keen to ensure that searchable database is
available to NSIs after end of ESSnet Admin Data.
SBS compared with IFRS definitions
• Building on information collected by the Eurostat
funded Taxonomy Project;
• Structural Business Statistics variables, because
financial statements tend to be produced annually.
• Many items in companies’ financial statements
look like SBS variables, but not precisely the same.
Work is continuing, but first recommendations are:
(a) SBS turnover definition should be amended to
exclude excise duties;
(b) Turnover; Changes in stocks of goods and
services; and Total purchases can be obtained
directly from the Notes to company accounts.
Estimation of missing SBS variables
1. Change in stocks of goods for resale – if total
change is available from financial statements,
robust regression modelling works well for the
breakdowns. Mass imputation (using nearest
neighbour donor imputation) works fairly well
when a small number of survey responses are
available but no admin data.
2. Purchases for resale in the same condition –
simple ratio estimation with VAT turnover data
works well provided a small number of survey
responses are available.
Estimation of missing SBS variables
3. No. of employees in full-time equivalents – simple
multiplication of total employees by a conversion
factor (obtained from hours worked or hours paid
survey data) works very well in practice;
4. Payments for agency workers – no helpful admin
data found;
5. Investment in tangible goods – current work on
how to estimate for details of capital investment
and disposals using admin data;
6. Production value - future work on how to estimate
production value.
Timeliness issues for STS
Admin data are often received too late for STS
delivery dates. There are two cases, based on how
much admin data are available:
1. admin data are fairly complete and can be
considered as representative STS estimates can be based only on admin data
2. admin data are incomplete and cannot be
considered as representative STS estimates can use admin data combined with
data from a survey of large enterprises
Timely admin data are not representative
Work is continuing to make firm recommendations
for best methods to use, depending on the precise
availability of admin data to the NSI. Three
approaches are being worked on currently • Monthly survey calibrated by VAT quarterly data;
• Time-series analyses for separate estimation for
small enterprises;
• Model-based: by comparing the growth rate for
large enterprises with that for the entire
population.
Quality Indicators
• Quantitative quality indicators, e.g.
- Under-coverage
- % of units in admin data which fail checks
- % of units for which data have been adjusted
• Background information indicators, e.g.
- % of required variables derived indirectly from
the admin data
- % of common units in more than one admin
source
• Composite indicators
• Qualitative quality indicators
Checklists
In order to produce the quality indicators, NSIs
must carry out several checks and record the
results. We are therefore producing a handbook
covering:
• Issues to consider before acquiring a new admin
dataset, and if an existing admin dataset changes
(e.g. a quarterly delivery becomes a monthly
delivery); and
• Best practice methods for initial cleaning of
admin datasets when received by the NSI.
Information Centre
The website address is: essnet.admindata.eu.
Future Workshops
SBS workshop – 20/21 March 2013 in Lisbon, PT
• current uses of admin data for SBS,
• relationship with admin data holder,
• initial cleaning of admin data for SBS,
• practical methods for making use of company
accounts data
• recommended quality indicators
Final STS workshop – 7 May 2013 in Tallinn, EE
Thank you for your attention
– any questions?