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Cano-Rodríguez, M (2025). How much is too much? Measuring divergence from Benford's Law with the Equivalent Contamination Proportion (ECP). Preprint arXiv:2506.09915 [econ.EM]; last accessed August 27, 2025.

This work cites the following items of the Benford Online Bibliography:


Amiram, D, Bozanic, Z and Rouen, E (2015). Financial statement errors: evidence from the distributional properties of financial statement numbers. Review of Accounting Studies 20(4), pp. 1540–1593. DOI:10.1007/s11142-015-9333-z. View Complete Reference Online information Works that this work references Works that reference this work
Ausloos, M, Cerqueti, R and Mir, TA (2017). Data science for assessing possible tax income manipulation: The case of Italy. Chaos, Solitons and Fractals 104, pp. 238–256. DOI:10.1016/j.chaos.2017.08.012. View Complete Reference Online information Works that this work references Works that reference this work
Badal-Valero, E, Alvarez-Jareño, JA and Pavía, JM (2018). Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case. Forensic Science International 282, pp. 24-34. DOI:10.1016/j.forsciint.2017.11.008. View Complete Reference Online information Works that this work references Works that reference this work
Balashov, VS, Yan, Y and Zhu, X (2021). Using the Newcomb–Benford law to study the association between a country’s COVID-19 reporting accuracy and its development. Scientific Reports 11, pp. 22914. DOI:10.1038/s41598-021-02367-z. View Complete Reference Online information Works that this work references Works that reference this work
Barabesi, L, Cerasa, A, Cerioli, A and Perrotta, D (2018). Goodness-of-fit testing for the Newcomb-Benford law with application to the detection of customs fraud. Journal of Business & Economic Statistics 36(2), pp. 346-358. DOI:10.1080/07350015.2016.1172014. View Complete Reference Online information Works that this work references Works that reference this work
Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572. View Complete Reference Online information No Bibliography works referenced by this work. Works that reference this work
Campanelli, L (2022). Tuning up the Kolmogorov-Smirnov test for testing Benford’s law. Preprint on ResearchGate; published in Comnunications in Statistics - Theory and Methods 2024. View Complete Reference Online information Works that this work references Works that reference this work
Campolieti, M (2022). COVID-19 deaths in the USA: Benford’s law and under-reporting. Journal of Public Health 44(2), pp. e268-e271. DOI:10.1093/pubmed/fdab161. View Complete Reference Online information Works that this work references Works that reference this work
Cano-Rodríguez, M, Núñez-Nickel, M and Licerán-Gutiérrez, A (2025). Divergence from Benford’s law fails to measure financial statement accuracy. International Journal of Accounting Information Systems 56, pp. 100745. DOI:10.1016/j.accinf.2025.100745. View Complete Reference Online information Works that this work references Works that reference this work
Cerasa, A (2022). Testing for Benford’s Law in very small samples: Simulation study and a new test proposal. PLoS ONE 17(7), pp. e0271969. DOI:10.1371/journal.pone.0271969. View Complete Reference Online information Works that this work references Works that reference this work
Cerqueti, R and Lupi, C (2021). Some New Tests of Conformity with Benford's Law. Stats 4(3), pp. 745-761. DOI:10.3390/stats4030044. View Complete Reference Online information Works that this work references Works that reference this work
Cerqueti, R and Lupi, C (2023). Severe testing of Benford's law. TEST 32(2), pp. 677-694. DOI:10.1007/s11749-023-00848-z. View Complete Reference Online information Works that this work references Works that reference this work
Cerqueti, R and Maggi, M (2021). Data validity and statistical conformity with Benford’s Law. Chaos, Solitons & Fractals 144, p. 110740 . DOI:10.1016/j.chaos.2021.110740. View Complete Reference Online information Works that this work references Works that reference this work
Chakrabarty, B, Moulton, PC, Pugachev, L and Wang, X (2024). Catch me if you can: In search of accuracy, scope, and ease of fraud prediction. Review of Accounting Studies. DOI:10.1007/s11142-024-09854-4. View Complete Reference Online information Works that this work references Works that reference this work
Cong, LW, Li, X, Tang, K and Yang, Y (2021). Crypto Wash Trading. Management Science 69(11), pp. 6427-6454. DOI:10.1287/mnsc.2021.02709. View Complete Reference Online information Works that this work references Works that reference this work
Diekmann, A (2007). Not the First Digit! Using Benford's Law to Detect Fraudulent Scientific Data. Journal of Applied Statistics 34(3), pp. 321-329. ISSN/ISBN:0266-4763. DOI:10.1080/02664760601004940. View Complete Reference Online information Works that this work references Works that reference this work
Eutsler, J, Harris, MK, Williams, LT and Cornejo, OE (2023). Accounting for partisanship and politicization: Employing Benford's Law to examine misreporting of COVID-19 infection cases and deaths in the United States. Accounting, Organizations and Society, in press. DOI:10.1016/j.aos.2023.101455. View Complete Reference Online information Works that this work references Works that reference this work
Fewster, RM (2009). A Simple Explanation of Benford's Law. American Statistician 63(1), pp. 26-32. DOI:10.1198/tast.2009.0005. View Complete Reference Online information Works that this work references Works that reference this work
Kaiser, M (2019). Benford’s Law As An Indicator Of Survey Reliability—Can We Trust Our Data?. Journal of Economic Surveys Vol. 00, No. 0, pp. 1–17. DOI:10.1111/joes.12338. View Complete Reference Online information Works that this work references Works that reference this work
Koch, C and Okamura, K (2020). Benford's Law and COVID-19 Reporting. Posted on SSRN April 28, 2020; last accessed November 17, 2020. Published in Econ Lett 2020;196(109973) . View Complete Reference Online information Works that this work references Works that reference this work
Kolias, P (2022). Applying Benford’s law to COVID-19 data: the case of the European Union. Journal of Public Health 44(2), pp. e221-e226. DOI:10.1093/pubmed/fdac005. View Complete Reference Online information Works that this work references Works that reference this work
Kossovsky, AE (2021). On the Mistaken Use of the Chi-Square Test in Benford’s Law. Stats 4(2), pp. 419–453. DOI:10.3390/stats4020027. View Complete Reference Online information Works that this work references Works that reference this work
Ley, E (1996). On the Peculiar Distribution of the US Stock Indexes' Digits. American Statistician 50(4), pp. 311-313. ISSN/ISBN:0003-1305. DOI:10.1080/00031305.1996.10473558. View Complete Reference Online information Works that this work references Works that reference this work
Michalski, T and Stoltz, G (2013). Do Countries Falsify Economic Data Strategically? Some Evidence That They Might. The Review of Economics and Statistics 95(2), pp. 591-616. DOI:10.1162/REST_a_00274. View Complete Reference Online information Works that this work references Works that reference this work
Morrow, J (2014). Benford’s Law, Families of Distributions and a Test Basis. Center for Economic Performance Discussion Paper No 1291. View Complete Reference Online information Works that this work references Works that reference this work
Nigrini, MJ (1996). A taxpayer compliance application of Benford’s law. Journal of the American Taxation Association 18(1), pp. 72-91. View Complete Reference Online information Works that this work references Works that reference this work
Nigrini, MJ (2011). Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations. John Wiley & Sons: Hoboken, New Jersey; (2nd edition published in 2020, isbn 978-1-119-58576-3). ISSN/ISBN:978-0-470-89046-2. View Complete Reference Online information Works that this work references Works that reference this work
Nigrini, MJ (2015). Persistent Patterns in Stock Returns, Stock Volumes, and Accounting Data in the U.S. Capital Markets. Journal of Accounting, Auditing & Finance, Vol. 30(4) pp. 541–557. DOI:10.1177/0148558X15584051. View Complete Reference Online information Works that this work references Works that reference this work
Riccioni, J and Cerqueti, R (2018). Regular paths in financial markets: Investigating the Benford’s law. Chaos, Solitons and Fractals 107, pp. 186-194. DOI:10.1016/j.chaos.2018.01.008. View Complete Reference Online information Works that this work references Works that reference this work
Sifat, I, Tariq, SA and van Donselaar, D (2024). Suspicious Trading in Nonfungible Tokens (NFTs). Information & Management 61(1), p. 103898. DOI:10.1016/j.im.2023.103898. View Complete Reference Online information Works that this work references Works that reference this work
Silva, AdeA and Gouvêa, MA (2023). Study on the effect of sample size on type I error, in the first, second and first-two digits excessmad tests. International Journal of Accounting Information Systems 48, p. 100599. DOI:10.1016/j.accinf.2022.100599. View Complete Reference Online information Works that this work references Works that reference this work
Vičič, J and Tošić, A (2022). Application of Benford’s law on cryptocurrencies. Journal of Theoretical and Applied Electronic Commerce Research 17(1), pp. 313-326. DOI:10.3390/jtaer17010016. View Complete Reference Online information Works that this work references Works that reference this work