IMF DQAF generic framework

The generic DQAF, below, serves as the umbrella for the dataset-specific frameworks. To date, the IMF has developed the DQAF for six macroeconomic datasets. Others have been developed or are underway, several in cooperation with the World Bank, UNESCO and other international organizations.

The IMF Data Quality Assessment Framework (DQAF) identifies quality-related features of governance of statistical systems, statistical processes, and statistical products. It is rooted in the UN Fundamental Principles of Official Statistics and grew out of the Special Data Dissemination Standard (SDDS) and General Data Dissemination System (GDDS), the IMF’s initiatives on data dissemination. The DQAF incorporates their good practices and is the result of intensive consultations. The DQAF provides a structure for assessing existing practices against best practices, including internationally accepted methodologies.

Content of the July 2003 Framework

The DQAF’s coverage of governance, processes, and products is organized around a set of prerequisites and five dimensions of data quality—assurances of integrity, methodological soundness, accuracy and reliability, serviceability, and accessibility. For each dimension, the DQAF identifies 3-5 elements of good practice, and for each element, several relevant indicators. Further, in a cascading structure, more detail and more concreteness tailored to the dataset are provided by focal issues and key points.

0. Prerequisites of quality

0.1 Legal and institutional environment—The environment is supportive of statistics

0.1.1 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 Resources—Resources are commensurate with needs of statistical programs.

0.2.1 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 Relevance—Statistics cover relevant information on the subject field.

0.3.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.

0.4 Other quality management—Quality is a cornerstone of statistical work.

0.4.1 Processes are in place to focus on quality.

0.4.2 Processes are in place to monitor the quality of the statistical program.

0.4.3 Processes are in place to deal with quality considerations in planning the statistical program.

1. Assurances of integrity

The principle of objectivity in the collection, processing, and dissemination of statistics is firmly adhered to.

1.1 Professionalism—Statistical policies and practices are guided by professional principles.

1.1.1 Statistics are produced on an impartial basis.

1.1.2 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 Transparency—Statistical policies and practices are transparent.

1.2.1 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 Advanced notice is given of major changes in methodology, source data, and statistical techniques.

1.3 Ethical standards—Policies and practices are guided by ethical standards.

1.3.1 Guidelines for staff behaviour are in place and are well known to the staff.

2. Methodological soundness

The methodological basis for the statistics follows internationally accepted standards, guidelines, or good practices.

2.1 Concepts and definitions— Concepts and definitions used are in accord with internationally accepted statistical frameworks.

2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.

2.2 Scope—The scope is in accord with internationally accepted standards, guidelines, or good practices.

2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.

2.3 Classification/sectorization—Classification and sectorization systems are in accord with internationally accepted standards, guidelines, or good practices.

2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.

2.4 Basis for recording—Flows and stocks are valued and recorded according to internationally accepted standards, guidelines, or good practices

2.4.1 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 reliability

Source data and statistical techniques are sound and statistical outputs sufficiently portray reality

3.1 Source data – Source data available provide an adequate basis to compile statistics.

3.1.1 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, classifications, valuation, and time of recording required.

3.1.3 Source data are timely.

3.2 Assessment of source data—Source data are regularly assessed.

3.2.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and non sampling error; the results of the assessments are monitored and made available to guide statistical processes.

3.3 Statistical techniques— Statistical techniques employed conform to sound statistical procedures

3.3.1 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 outputs— Intermediate results and statistical outputs are regularly assessed and validated.

3.4.1 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 studies— Revisions, as a gauge of reliability, are tracked and mined for the information they may provide.

3.5.1 Studies and analyses of revisions are carried out routinely and used internally to inform statistical processes (see also 4.3.3).

4. Serviceability

Statistics, with adequate periodicity and timeliness, are consistent and follow a predictable revisions policy.

4.1 Periodicity and timeliness— Periodicity and timeliness follow internationally accepted dissemination standards.

4.1.1 Periodicity follows dissemination standards.

4.1.2 Timeliness follows dissemination standards.

4.2 Consistency— Statistics are consistent within the dataset, over time, and with major datasets.

4.2.1 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 practice—Data revisions follow a regular and publicized procedure.

4.3.1 Revisions follow a regular and transparent schedule.

4.3.2 Preliminary and/or revised data are clearly identified.

4.3.3 Studies and analyses of revisions are made public (see also 3.5.1)

5. Accessibility

Data and metadata are easily available and assistance to users is adequate.

5.1 Data accessibility— Statistics are presented in a clear and understandable manner, forms of dissemination are adequate, and statistics are made available on an impartial basis.

5.1.1 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 pre-announced 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 accessibility— Up-to-date and pertinent metadata are made available.

5.2.1 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 users— Prompt and knowledgeable support service is available.

5.3.1 Contact points for each subject field are publicized.

5.3.2 Catalogues of publications, documents, and other services, including information on any changes, are widely available.

See also

• Mapping: NQAF to IMF DQAF