Information Content of DQAF Indicators; Empirical Entropy Analysis
The study presents an analysis of the information content of IMFâ€™s Data Quality Assessment Framework (DQAF) indicators. There are significant differences in the quantity of information between DQAF dimensions and sub-dimensions. The most informative DQAF dimension is accessibility, followed by the prerequisites of quality and accuracy and reliability. The least informative DQAF dimensions are serviceability and assurances of integrity. The implication of these findings is that the current DQAF indicators do not maximize the amount of information that could be obtained during data ROSC missions. An additional set of assessments that would refine the existing DQAF indicators would be beneficial in maximizing the information gathered during data ROSC mission. The entropy of DQAF indicators could also be used in the construction of a cardinal index of data quality.
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- Jochen Hartwig, 2007.
"Trying to Assess the Quality of Macroeconomic Data – the Case of Swiss Labour Productivity Growth as an Example,"
KOF Working papers
07-173, KOF Swiss Economic Institute, ETH Zurich.
- Jochen Hartwig, 2009. "Trying to assess the quality of macroeconomic data: The case of Swiss labour productivity growth as an example," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(1), pages 37-61.
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