2. Overview of the General Data Dissemination System
- International Monetary Fund. Statistics Dept.
- Published Date:
- December 2013
Purposes and Framework of the GDDS
2.1 The purposes of the GDDS are to: (i) encourage member countries to improve data quality; (ii) guide member countries in the provision to the public of comprehensive, timely, accessible, and reliable economic, financial, and sociodemographic statistics; and (iii) provide a framework for evaluating needs for data improvement and dissemination as well as for setting statistical priorities. The GDDS framework comprises four dimensions described in detail ahead: (1) coverage, periodicity, and timeliness of data; (2) access by the public; (3) integrity of the disseminated data; and (4) quality of the disseminated data. For each of the four dimensions, the GDDS describes good practices to serve as objectives in the development of national systems of data production and dissemination.
Coverage, Periodicity, and Timeliness of Data
2.2 The dissemination of reliable, comprehensive, and timely economic, financial, and sociodemographic data is essential to the transparency of macroeconomic performance and policy. The GDDS includes the following definitions and general considerations:
2.3 The GDDS focuses on the data that are most important in evaluating performance and policy in four macroeconomic sectors—real, fiscal, financial, and external—as well as complementary sociodemo-graphic data that shed light on economic development and structural change. The sociodemographic data specified under the GDDS are closely aligned with the majority of the indicators used to monitor progress toward the MDGs.1 The GDDS also covers most of the indicators used to monitor progress on national poverty reduction strategies. Table 1 in Chapter 3 shows the GDDS recommended data categories, including comprehensive statistical frameworks, tracking categories, and other relevant data, as appropriate, and highlights the main GDDS components and encouraged extensions.
Periodicity and Timeliness
2.4 The GDDS recognizes the importance of production and dissemination of data that are of appropriately high periodicity and timeliness.
2.5 Periodicity refers to the frequency of compilation of the data (i.e., the relevant period covered by a data observation, e.g., annual, quarterly, monthly, weekly, daily, etc.). The periodicity of a particular data category reflects several factors, including the ease of data collection and compilation, and the needs of analysis. The GDDS should be viewed as encouraging improvements over time in periodicity of data dissemination (i.e., it encourages higher frequency) that are consistent with improvements in data quality.
2.6 Timeliness refers to the speed of dissemination of the data, which refers to the lapse of time between a reference date (or close of a reference period) and dissemination of the data. It reflects many factors, including institutional arrangements, such as the preparation of accompanying commentary. Dissemination of statistics takes several forms, including the following:
Formal publications, such as news releases (perhaps presenting only summary statistics), periodicals such as monthly bulletins, or one-time volumes
Announcement of availability of statistics on request (but not necessarily without charge), including through electronic databases
The Internet, diskettes, tapes, or DVD/CD-ROM of a formal publication or a database
Recorded brief telephone messages, e-mail and fax services, especially in the case of data categories justifying high-frequency distribution
2.7 The objectives for timeliness that are presented in Table 1 in Chapter 3 are set out in terms of ranges of time in recognition of the diversity of relevant country practices and circumstances. The short end of the timeliness range generally corresponds to the SDDS timeliness requirement for a given indicator while the high end of the range relates to good practice across a broad group of countries.
Access by the Public
2.8 Dissemination of official statistics is an essential feature of statistics as a public good. Ready and equal access is a principal need for the public, including market participants. To support ready and equal access, the GDDS recommends the following:
Advance Dissemination of Release Calendars
2.9 ARCs2 highlight sound management and transparency of statistical compilation and provide data users with information needed to take a more active and organized approach to acquiring the inputs for their work. The objective may be met by the dissemination of calendars showing release dates for the current month and for the following three months. Agencies are recommended to make widely known the name and address of an office or a person who could provide the latest information about the ARC, including release of data for which periodicity and timeliness are irregular, and newly disseminated data.
Simultaneous Release to All Interested Parties
2.10 To recognize that data are valuable commodities and in the interest of equity, the GDDS recommends the release of data to all interested parties at the same time. Release is not intended to refer to access only by government agencies, including those other than the producing agency; prerelease access is governed by conditions set out in the description of integrity (see paragraph 2.15). The act of release may consist of providing summary data, to be accompanied, perhaps later, by provision of detail. The objective may be met by providing at least one publicly identified and accessible location where data are available to all on an equal basis once they are released.
2.11 Therefore, given the ongoing global integration and increased reliance on the Internet and electronic data transmission, the GDDS recommends releasing data simultaneously to the public through a NSDP3 that is published on the website of one of the statistics compiling agencies (see paragraph 9.2).
2.12 In order to further enhance the access by the public to the data, the data categories on the NSDP may be hyperlinked to a database where data are:
Freely available in a variety of standard, editable, and machine-readable electronic file formats, interfaces, and bulk forms
Freely available under a license that permits use, reuse, and redistribution for commercial and noncommercial purposes with the requirement of proper attribution
2.13 To fulfill the purpose of providing the public with information, official statistics must have the confidence of their users. In turn, confidence in the statistics ultimately becomes a matter of confidence in the objectivity and professionalism of the agency producing the statistics. Transparency of its practices and procedures is a key factor in creating this confidence. To assist users of the data disseminated under the GDDS in assessing their integrity, the GDDS recommends the following:
(1) Dissemination of the terms and conditions under which official statistics are produced, including those relating to the confidentiality of individually identifiable information
2.14 This practice, which was embodied in the Fundamental Principles of Official Statistics adopted in 1994 by the United Nations Statistical Commission, is indirect, but nevertheless fundamental to fostering confidence in the objectivity and professionalism of official statistics. The terms and conditions under which statistical agencies operate may take various forms, including statistics laws, charters, and codes of conduct. Accordingly, a first step toward this objective would be to put such laws, charters, and codes in place. The terms and conditions incorporated in them may refer to matters such as the relationship of the statistical unit to a larger department or ministry of which it is part (if relevant), the legal authority to collect data, the requirement to publish data it has collected, the terms of reference for the chief statistician/director, and procedures and processes related to confidentiality of individual responses. Dissemination of this information may take a variety of forms, including annual reports of the producers of statistics, abstracts in key publications, and statements of relevant passages referring to confidentiality of survey forms. Statistics producers may find it convenient to use logos and other insignia to remind users of the terms under which statistics carrying the logo are produced. These terms and conditions should be kept up-to-date.
(2) Identification of internal government access to data before release
2.15 In the interest of transparency about possible undue influence on the data before release, the GDDS calls for listing the persons/positions within the government, but outside the agency producing the data, who have prerelease access. Such identification—that is, statements of who knows what—may take a variety of forms, including brief notices to the public and annual reports of the producer of statistics. This practice is addressed mainly to situations in which the data are sensitive for policy or other reasons, and the objective may be met, at a minimum, by following this practice for the most sensitive data categories and indicators.
(3) Identification of ministerial commentary on the occasion of statistical releases
2.16 Ministerial commentary is not necessarily expected to maintain the same degree of objectivity or freedom from political judgment as would be expected of good practice for a producer of official statistics. Therefore, a good practice is to identify such commentary so that its source will be transparent to the public. The identification of ministerial commentary on the occasion of statistical release may take several forms, including separate statements by the minister (or other policy or political official) or, alternatively, identification of a statistical agency’s material in a release that contains both ministerial commentary and data. The agency’s material may include data, explanatory text (e.g., of an unusual event affecting the data), and objective analysis; the identification of an agency’s material may be made in various ways, including the use of source lines in tables and of the producer’s logos or other insignia. This practice is addressed mainly to situations in which the data are sensitive for policy or other reasons, and the objective may be met, at a minimum, by following this practice for the most sensitive data categories and indicators.
(4) Provision of information about revision and advance notice of major changes in methodology
2.17 In the interest of transparency about the data producers’ practices, the GDDS calls for the provision of information about past revisions and about major prospective sources of revision. Relevant information about revisions in data may include statements about the policy followed (e.g., a policy of revising monthly data when an annual, more comprehensive survey becomes available or a policy of no revision) and data about the size of past revisions; both policies and data on revisions may have to be developed before they can be disseminated. Changes in methodology (e.g., changes in base year, major expansions of sample size, introduction of alternative data sources, reclassification of transactions or industries) are to be expected in developing statistical systems. The advance notices may take a variety of forms, including, at a minimum, a short statement in the last presentation of unrevised data or on a stand-alone basis. These statements would identify the kinds of changes to be made and give a source for additional information, such as a paper available on request or the name and address of a person able to explain the upcoming change. Participants are encouraged, as well, to provide easy access to this type of information explaining revisions after they are released.
2.18 Data quality must have a high priority. Data users should be provided with information to assess quality and quality improvements. GDDS participants are encouraged to adopt and implement internationally accepted statistical methodologies for the data categories covered by the GDDS and are encouraged to indicate where statistical practices deviate from these methodologies (a specified list of these methodologies is posted on the DSBB; see http://dsbb.imf.org/pages/SDDS/statmethod.aspx). Although quality is difficult to judge, monitorable proxies, designed to focus on information the user needs to judge quality, can be useful. To assist users of the data disseminated under the GDDS in assessing their quality, the GDDS recommends the following:
(1) Dissemination of documentation on methodology and sources used in preparing statistics
2.19 The availability of documentation on methodology and sources underlying statistics is key to users’ awareness of the strengths and weaknesses of the data. In addition to information on the DSBB, the participant’s documentation may take several forms, including summary notes accompanying release of the data, separate publications, and papers available on request from the producers. GDDS participants are encouraged to prepare and disseminate statements about important features of quality (e.g., the kinds of errors to which the data are subject, sources of noncomparability over time, and measures of coverage for census data or sample error for survey data).4
(2) Dissemination of component detail, reconciliations with related data, and statistical frameworks that support statistical cross-checks and provide assurance of reasonableness
2.20 To support and encourage users’ checks and verification of data, this element provides for dissemination of components underlying aggregate series, dissemination within a statistical framework, and/or dissemination of comparisons and reconciliations with related data. Component detail should be at a level that does not conflict with other desirable characteristics, such as the confidentiality of individually identifiable information or statistical reliability. Statistical frameworks include accounting identities and statistical relationships (such as matching stocks with flows). Comparisons and reconciliations include those that cut across frameworks, such as exports and imports as part of the national accounts and as part of the balance of payments.
ARCs are required under the SDDS.
NSDPs are required under the SDDS.
The size of past revisions, which is an important aspect of quality, also is included under integrity, drawing on its role as an indicator of the transparency of conditions under which data are produced.