The Use of Administrative
Sources for Economic Statistics
An Overview
Steven Vale
Office for National Statistics
UK
Contents
• Definitions
• Advantages of using administrative
data
• Common problems
• Quality of administrative data
• Using administrative data in practice
• Conclusions
Narrow Definition
Data Sources
Primary
(Statistical)
Secondary
(Non-statistical)
Public
Sector
Private
Sector
Wider Definition
Data Sources
Primary
(Statistical)
Secondary
(Non-statistical)
Public
Sector
Private
Sector
Administrative sources
are sources containing
information which is not
primarily collected for
statistical purposes.
Reasons for this Definition
• Privatisation of some government
functions
• Growth of private sector “value-added
re-sellers”
• User interest in new types of data
Benefits of Administrative Data
• Cost
– Surveys / censuses are expensive,
administrative data are often “free”
• Response burden
– Reduced burden on data suppliers
– Statistics can be compiled more
frequently with no extra burden
Benefits of Administrative Data
• Coverage
– Full coverage of target population
– No survey errors and lower non-response
– Better small-area data
• Timeliness (sometimes!)
• Public image
– Making use of existing data can enhance
the prestige of a statistical organisation by
making it seem more efficient
Population Census Costs
2000-2001
• UK, €367m, €6.2 per person
• Austria, €56m, €6.9 per person
• Finland, €0.8m, €0.2 per person
Source: Eurostat – Documentation of the 2000
round of population and Housing censuses in the
EU, EFTA and Candidate Countries; Table 22
Common Problems
• Administrative units do not always
coincide with statistical units
• Conversion via automatic rules for
simple cases
• Profiling for more complex cases
– Gives a better understanding of
complex business structures
– Expensive and needs trained staff
Common Problems
• Different definitions and classifications
– Administrative and statistical priorities are
often different
– Conversion matrices needed for different
classifications
• Timeliness
– Data arrive too late
– Data relate to a different time period
Lag in days
1000
950
900
850
800
750
700
650
600
550
500
450
400
350
300
250
200
150
100
50
0
Frequency (thousands)
VAT Birth Lags
200
180
160
140
120
100
80
60
40
20
0
VAT Birth Lags
• 2/3 of businesses are on the register
within 2 months of start-up
• Mean lag = 4 months due to “outliers”
• Median = Approx. 40 days
• Some pre-register - negative lags
Common Problems
• Change management
– Risk of changes in government policy,
thresholds, definitions, coverage etc.
– Need contingency plans
• Data from multiple sources
– Matching / linking issues
– Data conflicts – priority rules
Quality of Administrative Data
• There are many aspects to quality
• Administrative data will be better than
survey data in some aspects but not
in others
• It is important to look at overall quality
• Do the data meet the needs of users?
Three Aspects of Quality
• Quality of incoming data
• Quality of processing
(matching, merging, ...)
• Quality of outputs - likely to be
different to survey based outputs,
but are they better?
Quality Measurement
• How to measure the quality of data
from administrative sources?
– Comparing sources
– Quality check surveys
– Knowledge of source (metadata)
– Quality reports / templates
Quality Templates
Companies House Data
• Framework: Contract
• Frequency: Quarterly updates, continuous
on-line access
• Timeliness: Good
• Quality:
Good
• Delivery:
CD-ROM / Internet
• Key content: Legal name, company number
Using Administrative Data
• Conversion to statistical concepts and
definitions
• Linking / Matching
– Exact Matching - linking records from
two or more sources, often using
common identifiers
– Probabilistic Matching - determining the
probability that records from different
sources should match, using a
combination of variables
UK Business Register
VAT
Survey
inputs
Satellite
registers
Company
registrations
Business
Register
PAYE
Geographic
information
systems
Dun and
Bradstreet
Satellite Registers
Examples of Satellite Registers
• Tourism - hotel register (category,
number of beds)
• Transport - vehicle or ship register
(type, capacity)
• Distributive trades - buildings register
(building size, sales area)
Conclusions
• Administrative sources should be
defined in the widest sense
• There are many benefits in using
administrative data, particularly
reduced costs
• There are problems when using
administrative data, but usually
someone has found a solution
Conclusions
• Most problems can be reduced by
effective planning and detailed
knowledge of the source
• The benefits are often greater than
the costs
Thank-you for listening.
Any Questions?
steve.vale@ons.gov.uk