Chapter

Appendix 4. Data Quality Assessment Framework (DQAF): Generic Framework (May 2012 version)

Author(s):
International Monetary Fund. Statistics Dept.
Published Date:
December 2013
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Table A4.1Data Quality Assessment Framework (Generic)
Quality DimensionsElementsIndicators
0. Prerequisites of quality0.1 Legal and institutional environment0.1.1 The responsibility for collecting, processing, and disseminating the statistics is clearly specified.
0.1.2 Data sharing and coordination among data-producing agencies are adequate.
0.1.3 Individual reporters’ data are to be kept confidential and used for statistical purposes only.
0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.
0.2 Resources0.2.1 Staff, facilities, computing resources, and financing are commensurate with statistical programs.
0.2.2 Measures to ensure efficient use of resources are implemented.
0.3 Relevance0.3.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.
0.4 Other quality management0.4.1 Processes are in place to focus on quality.

0.4.2 Processes are in place to monitor quality during the planning and implementation of the statistical program.
1. Assurances of1.1 Institutional integrity1.1.1 Statistics are produced on an impartial basis.
integrity1.1.2 Choices of sources and statistical techniques, as well as decisions about dissemination, are informed solely by statistical considerations.
1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.
1.2 Transparency1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.
1.2.2 Internal governmental access to statistics prior to their release is publicly identified.
1.2.3 Products of statistical agencies/units are clearly identified as such.
1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.
1.3 Ethical standards1.3.1 Guidelines for staff behavior are in place and are well known to the staff.
2. Methodological soundness2.1 Concepts and definitions2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.
2.2 Scope2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.
2.3 Classification/ sectorization2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.
2.4 Basis for recording2.4.1 Market prices are used to value flows and stocks.
2.4.2 Recording is done on an accrual basis.
2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.
3. Accuracy and reliability3.1 Source data3.1.1 Source data are obtained from comprehensive data collection programs that take into account country-specific conditions.
3.1.2 Source data reasonably approximate the definitions, scope, sectorization, classifications, valuation, and time of recording required.
3.1.3 Source data are timely.
3.2 Assessment of source data3.2.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide statistical processes.
3.3 Statistical techniques3.3.1 Data compilation employs sound statistical techniques to deal with data sources.
3.3.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.
3.4 Assessment and validation of intermediate data and statistical outputs3.4.1 Intermediate results are validated against other information, where applicable.
3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.
3.4.3 Statistical discrepancies and other potential indicators or problems in statistical outputs are investigated.
3.5 Revision studies3.5.1 Studies and analyses of revisions and/or updates are carried out routinely and used internally to inform statistical processes (see also 4.3.3).
4. Serviceability4.1 Periodicity and timeliness4.1.1 Periodicity follows dissemination standards.
4.1.2 Timeliness follows dissemination standards.
4.2 Consistency4.2.1 Statistics are consistent within the dataset.
4.2.2 Statistics are consistent or reconcilable over a reasonable period of time.
4.2.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.
4.3 Revision policy and practice4.3.1 Revisions and/or updates follow a regular and transparent schedule.
4.3.2 Preliminary and/or revised/updated data are clearly identified.
4.3.3 Studies and analyses of revisions are made public (see also 3.5.1).
5. Accessibility5.1 Data accessibility5.1.1 Statistics are presented in a way that facilitates proper
interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).
5.1.2 Dissemination media and format are adequate.
5.1.3 Statistics are released on a preannounced schedule.
5.1.4 Statistics are made available to all users at the same time.
5.1.5 Statistics not routinely disseminated are made available upon request.
5.2 Metadata accessibility5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.
5.2.2 Levels of detail are adapted to the needs of the intended audience.
5.3 Assistance to users5.3.1 Contact points are publicized.
5.3.2 Catalogs of publications, documents, and other services, including information on any charges, are widely available.
Source: IMF staff.

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