International Journal of Auditing Technology 4(4), pp. 279-291.
ISSN/ISBN: Not available at this time. DOI: 10.1504/IJAUDIT.2022.10047587
Abstract: Despite common belief, most datasets do not conform perfectly to Benford\'s law; they fail famous Benford tests in the literature, or as Nigrini puts it, these tests are too powerful for checking the conformity. We propose a new approach on measuring the deviation of datasets from Benford distribution to determine possible abnormality. We show that the conventional digit frequency tests do not fully absorb the \"significant digit\" property mainly when the number of samples is too small or too large. We then propose our method using the logarithmic basis of Benford\'s law which states the mantissa of the logarithm of all practical numbers should be uniformly distributed. We then test several goodness-of-fit techniques that compare the sample data\'s mantissa distribution with that of the uniform distribution between zero and one. Our experiment show that Kolmogrov-Smirnov test for uniformity works best for small, medium size and even large records.
Bibtex:
@article{,
author = {Javad Kazemitabar and Jalil Kazemitabar},
title = {Benford Test Based on Logarithmic Property},
year = {2022},
journal = {International Journal of Auditing Technology},
volume = {4},
number = {4},
pages = {279--291},
doi = {10.1504/IJAUDIT.2022.10047587},
}
Reference Type: Journal Article
Subject Area(s): Accounting