Data Quality Reference Site

Introduction to the Data Quality Reference Site

The Data Quality Reference Site (DQRS) is part of the IMF's ongoing effort to stimulate dialogue and develop a common understanding of data quality. Drawing from the IMF's own experience in macroeconomic statistics and from contributions from the statistical community, the site introduces definitions of data quality, describes trade-offs among aspects of data quality, and gives examples of evaluations of data quality.

The DQRS also seeks to support different approaches to data quality (Approaches to Data Quality), provides references (Reference Materials), makes available work in progress by IMF staff (Work in Progress by IMF Staff), supplies information on current conferences and meetings on economic data quality (Conferences and Meetings on Data Quality), makes available links to related sites (Links to Related Sites), provides links to Reports on the Observances of Standards and Codes data modules (ROSCs ) and provides information on the IMF Data Quality Assessment Framework (DQAF ).

This site is expected to evolve over time. Questions, comments, and suggestions, including suggestions about additions are welcome.

A key contribution of the IMF to data quality is the Special Data Dissemination Standard (SDDS). The SDDS identifies best practices in the dissemination of economic and financial data in four areas, the so-called four dimensions: data coverage, periodicity and timeliness, public access to the data, integrity of the data, and data quality. In this context, quality refers to characteristics such as accuracy, adherence to international statistical guidelines, and consistency. The General Data Dissemination System (GDDS) takes a similar approach to data quality, placing more emphasis on improving data quality over the long run.

Further, the IMF has prepared a framework for assessing the quality of data used for macroeconomic analysis. The Data Quality Assessment Framework (DQAF) provides an integrated and flexible framework in which data quality is assessed using a six-part structure that spans institutional environments, statistical processes, and characteristics of the statistical products.