New Zealand Journal of Marine and Freshwater Research Volume 43, Issue 1, pp. 457-463.
ISSN/ISBN: Not available at this time. DOI: 10.1080/00288330909510014
Abstract: In this study we introduce the first step towards a statistical model for the reliability of fisheries data. We applied Benford's Law to catch data from the Atlantic Canadian lobster (Homarus americanus) fishery's lobster fishery areas (LFAs) 33 and 34 and compared our results to those using observations from the “grey zone” (a highly regulated lobster fishery shared by Canada and United States) and a fishery with a different regulatory regime (snow crab, Chionoecetes opilio). Non-conformity with Benford's Law is often considered as an indicator of human manipulation of accounting data. We found that observations from the grey zone conformed to the distribution predicted by Benford's Law, whereas observations from snow crab and both lobster fishery areas did not conform.
Bibtex:
@article{,
author = {Scott D. J. Graham and John Hasseldine and David Paton },
title = {Statistical fraud detection in a commercial lobster fishery},
journal = {New Zealand Journal of Marine and Freshwater Research},
volume = {43},
number = {1},
pages = {457--463},
year = {2009},
publisher = {Taylor & Francis},
doi = {10.1080/00288330909510014},
URL = {http://www.tandfonline.com/doi/abs/10.1080/00288330909510014 },
}
Reference Type: Journal Article
Subject Area(s): Accounting, Statistics