Challenges with classifications
based on country contributions
19-21 March 2013, Kishinev,
Moldova
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Main issues with classifications
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Long delays in updating classifications
Coordination of classification changes –
adaptation to national circumstances
Insufficient resources and programming
Quality monitoring – harmonized tools
Time series breaks – loss of information
More information about classifications to users
Implementing classifications in practice
Knowledge in back-casting methodology
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“The use by statistical agencies in each
country of international concepts,
classifications and methods promotes
the consistency and efficiency of
statistical systems at all official levels.”
The ninth principle of The Fundamental Principles of Official Statistics
in the Region of the Economic Commission for Europe, UNECE
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Delays in updating
classifications
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In many countries delays of 4-5 years
Classifications in Russian available with a delay
Lack of practical guidelines in Russian
Scarce resources dedicated to classifications
Insufficient training opportunities for staff
Coordination within NSO and government takes time
Inflexible legislative processes delay the work
Practical guidance is needed for changeovers
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Coordination of classification
changes
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Often different agencies are in charge of
classifications typical for their area of work
NSOs should have a stronger coordination role over
the use and development of statistical classifications
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With other producers of official statistics
With government offices using classifications
With tax administration dealing with classifications
Would help to maintain consistency of statistics
Consultations are needed to adapt classifications at
the detailed levels to national needs
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Insufficient resources and
programming
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Sometimes no or a small organizational unit with the
responsibility for classification issues
Changeover should be planned as a stepwise project
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Timetable needs to be agreed across producers of statistics as
statistics are interconnected
Data collection and compilation tools and procedures to be adapted
A working group or several are needed
Re-calculation is often quite resource intensive
Resource constraints cause delays → poor comparability
Training of experts:
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Across statistics before the changeover
Training also for regular implementation of classifications
Users and other producers also need training
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Quality monitoring –
harmonized tools
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A database on classifications is available in some countries to
respondents and users for downloading
Metadata is easier to use if its structure is harmonized
Classifications database saves resources and can be used in
compilation of different statistics within the NSS
Changes needed to surveys and compilation tools have to be
reviewed early
Common policy or instructions for methods to be used
Updating a classification is a chance for reviewing the quality
of classification codes of units – the same code should be
used across statistics
Correspondence tables and dual coding are examples of
essential tools in classification changes
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Avoiding loss of information
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Time series should be calculated backwards
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Classification changes are important, while you should
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Not many practical guidelines available
Take all possible steps to minimise unnecessary changes to
data compilation and classifications
Develop procedures to reduce the frequency of revisions
Sometimes time series may be disrupted when
outdated classifications, concepts and questionnaires
are maintained for too long and linking becomes
difficult
There is a trade-off between costs imposed by
breaking a time series on one hand and the benefits
from improving the relevance of the time series
*Recommendations from the OECD data and metadata reporting and presentation handbook
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Time series breaks
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A break may be the result of a single change or the
combination of multiple changes at any one point in
time of observation of the variable. The specific
causes of breaks in a statistical time series include
changes in: classifications used, definitions of the
variable, coverage; etc.
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Attempt to revise the historical series as far back as
data and available resources permit!
*Recommendations from the UNECE Metadata Common Vocabulary, 2008.
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Metadata on classifications
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All statistical agencies should:
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compile metadata required for users to understand the
strengths and limitations of the statistics it describes; and
keep their metadata up-to-date, incorporating the latest
changes in definitions, classifications and methodology, etc.
The precise name of the classification used should
always be clearly indicated (for instance, NACE Rev. 2
or the name of national classification) so that the user
clearly knows which classification has been used
Provide advance notice of major changes in concepts,
definitions, and classification and methods
*Recommendations from the OECD data and metadata reporting and presentation handbook
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Informing about series breaks
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Where significant breaks are unavoidable, users
should be given warning well in advance
Give the timing of implementation and a detailed
explanation of the reasons for the change
Allow sufficient time for users to implement
modifications to their systems, programmes or
databases and to seek further clarification
Actual breaks in the series should be clearly identified
in both the statistical table and any accompanying
graphs
The break should be completely visible to users
*Recommendations from the OECD data and metadata reporting and presentation handbook
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Explaining series breaks
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Reference period where the break occurred
Is it a one-off break with limited implications for the
time series and / or has it led to adjustment
Precise outline of the difference in concepts and
methods of measurement before and after the break
Description of the cause(s) of the difference, e.g.
changes in classification, in statistical methodology,
statistical population etc.
Assessment of the magnitude of the effect of the
change, where possible, with a quantitative measure
Reference to more detailed information
*Recommendations by Eurostat in Methodological Documents: Standard Report, 2003.
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Presenting data with a break
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Points in line graphs should not be joined across
discontinuities in data
Explain the reason for the break in a footnote
Refer to more detailed explanations
*Recommendations by Eurostat in Methodological Documents: Standard Report, 2003.
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