IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2009-010.html
   My bibliography  Save this paper

Benford’s Law and Macroeconomic Data Quality

Author

Listed:
  • Mr. Gonzalo C Pastor Campos
  • Mr. Jesus R Gonzalez-Garcia

Abstract

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.

Suggested Citation

  • Mr. Gonzalo C Pastor Campos & Mr. Jesus R Gonzalez-Garcia, 2009. "Benford’s Law and Macroeconomic Data Quality," IMF Working Papers 2009/010, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2009/010
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=22581
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eduardo Ley, 1995. "On the Peculiar Distribution of the U.S. Stock Indeces' Digits," Finance 9503002, University Library of Munich, Germany.
    2. 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).
    3. 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.
    4. Andreas Diekmann, 2005. "Not the First Digit! Using Benford’s Law to Detect Fraudulent Scientific Data," Others 0507001, University Library of Munich, Germany.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. T. Mir, 2016. "The leading digit distribution of the worldwide illicit financial flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 271-281, January.
    2. T. A. Mir, 2016. "The leading digit distribution of the worldwide illicit financial flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 271-281, January.
    3. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    4. Huang, Yasheng & Niu, Zhiyong & Yang, Clair, 2020. "Testing firm-level data quality in China against Benford’s Law," Economics Letters, Elsevier, vol. 192(C).
    5. Koch, Christoffer & Okamura, Ken, 2020. "Benford’s Law and COVID-19 reporting," Economics Letters, Elsevier, vol. 196(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. T. A. Mir, 2016. "The leading digit distribution of the worldwide illicit financial flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 271-281, January.
    2. Brähler, Gernot & Bensmann, Markus & Emke, Anna-Lena, 2010. "Der Einsatz mathematisch-statistischer Methoden in der digitalen Betriebsprüfung," Ilmenauer Schriften zur Betriebswirtschaftslehre, Technische Universität Ilmenau, Institut für Betriebswirtschaftslehre, volume 4, number 42010.
    3. Theoharry Grammatikos & Nikolaos I. Papanikolaou, 2021. "Applying Benford’s Law to Detect Accounting Data Manipulation in the Banking Industry," Journal of Financial Services Research, Springer;Western Finance Association, vol. 59(1), pages 115-142, April.
    4. Vadim S. Balashov & Yuxing Yan & Xiaodi Zhu, 2020. "Who Manipulates Data During Pandemics? Evidence from Newcomb-Benford Law," Papers 2007.14841, arXiv.org, revised Jan 2021.
    5. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    6. McDonald, Bruce D. III & Goodman, Christopher B, 2020. "The Truth about Honesty in the Nonprofit Sector," SocArXiv 48g5c, Center for Open Science.
    7. Montag, Josef, 2017. "Identifying odometer fraud in used car market data," Transport Policy, Elsevier, vol. 60(C), pages 10-23.
    8. T. Mir, 2016. "The leading digit distribution of the worldwide illicit financial flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 271-281, January.
    9. Montag, Josef, 2015. "Identifying Odometer Fraud: Evidence from the Used Car Market in the Czech Republic," MPRA Paper 65182, University Library of Munich, Germany.
    10. Lee, Joanne & Judge, George G, 2008. "Identifying falsified clinical data," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt8x00h1c1, Department of Agricultural & Resource Economics, UC Berkeley.
    11. Bernhard Rauch & Max Göttsche & Gernot Brähler & Stefan Engel, 2011. "Fact and Fiction in EU‐Governmental Economic Data," German Economic Review, Verein für Socialpolitik, vol. 12(3), pages 243-255, August.
    12. Hansen, Bradley A. & Hansen, Mary Eschelbach, 2016. "The historian's craft and economics," Journal of Institutional Economics, Cambridge University Press, vol. 12(2), pages 349-370, June.
    13. Tariq Ahmad Mir & Marcel Ausloos & Roy Cerqueti, 2014. "Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions," Papers 1410.2890, arXiv.org.
    14. Ioana Sorina Deleanu, 2017. "Do Countries Consistently Engage in Misinforming the International Community about Their Efforts to Combat Money Laundering? Evidence Using Benford’s Law," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-19, January.
    15. Dominique Geyer & Christoph Drechsler, 2014. "Detecting Cosmetic Debt Management Using Benford's Law," Post-Print hal-01059758, HAL.
    16. Ronelle Burger & Canh Thien Dang & Trudy Owens, 2017. "Better performing NGOs do report more accurately: Evidence from investigating Ugandan NGO financial accounts," Discussion Papers 2017-10, University of Nottingham, CREDIT.
    17. Bogdan Vasile Ileanu & Marcel Ausloos & Claudiu Herteliu & Marian Pompiliu Cristescu, 2019. "Intriguing behavior when testing the impact of quotation marks usage in Google search results," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2507-2519, September.
    18. Villas-Boas, Sofia B. & Fu, Qiuzi & Judge, George, 2017. "Benford’s law and the FSD distribution of economic behavioral micro data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 711-719.
    19. Auffhammer, Maximilian & Carson, Richard T., 2008. "Forecasting the path of China's CO2 emissions using province-level information," Journal of Environmental Economics and Management, Elsevier, vol. 55(3), pages 229-247, May.
    20. Ragui Assaad & Caroline Krafft & Shaimaa Yassin, 2018. "Comparing retrospective and panel data collection methods to assess labor market dynamics," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 1-34, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:imf:imfwpa:2009/010. 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: . General contact details of provider: https://edirc.repec.org/data/imfffus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.