Benfordâ€™s Law and Macroeconomic Data Quality
This paper examines the usefulness of testing the conformity of macroeconomic data with Benford's law as indicator of data quality. Most of the macroeconomic data series tested conform with Benford's law. However, questions emerge on the reliability of such tests as indicators of data quality once conformity with Benford's law is contrasted with the data quality ratings included in the data module of the Reports on the Observance of Standards and Codes (data ROSCs). Furthermore, the analysis shows that rejection of Benford's law may be unrelated to the quality of statistics, and instead may result from marked structural shifts in the data series. Hence, nonconformity with Benford's law should not be interpreted as a reliable indication of poor quality in macroeconomic data.
|Date of creation:||01 Jan 2009|
|Date of revision:|
|Contact details of provider:|| Postal: International Monetary Fund, Washington, DC USA|
Phone: (202) 623-7000
Fax: (202) 623-4661
Web page: http://www.imf.org/external/pubind.htm
More information through EDIRC
|Order Information:||Web: http://www.imf.org/external/pubs/pubs/ord_info.htm|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- George Judge & Laura Schechter, 2009. "Detecting Problems in Survey Data Using Benford’s Law," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
- Nye John & Moul Charles, 2007. "The Political Economy of Numbers: On the Application of Benford's Law to International Macroeconomic Statistics," The B.E. Journal of Macroeconomics, De Gruyter, vol. 7(1), pages 1-14, July.
- Eduardo Ley, 1995. "On the Peculiar Distribution of the U.S. Stock Indeces' Digits," Finance 9503002, EconWPA.
- Hill, Theodore P. & Schürger, Klaus, 2005. "Regularity of digits and significant digits of random variables," Stochastic Processes and their Applications, Elsevier, vol. 115(10), pages 1723-1743, October.
- Andreas Diekmann, 2007.
"Not the First Digit! Using Benford's Law to Detect Fraudulent Scientif ic Data,"
Journal of Applied Statistics,
Taylor & Francis Journals, vol. 34(3), pages 321-329.
- Andreas Diekmann, 2005. "Not the First Digit! Using Benford’s Law to Detect Fraudulent Scientific Data," Others 0507001, EconWPA.
When requesting a correction, please mention this item's handle: RePEc:imf:imfwpa:09/10. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jim Beardow)or (Hassan Zaidi)
If references are entirely missing, you can add them using this form.