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Benford's Law and the Detection of Election Fraud

Published online by Cambridge University Press:  04 January 2017

Joseph Deckert
Affiliation:
University of Oregon 97403 and California Institute of Technology 91124
Mikhail Myagkov
Affiliation:
University of Oregon 97403 and California Institute of Technology 91124
Peter C. Ordeshook*
Affiliation:
University of Oregon 97403 and California Institute of Technology 91124
*
e-mail: ordeshook@hss.caltech.edu (corresponding author)
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Abstract

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The proliferation of elections in even those states that are arguably anything but democratic has given rise to a focused interest on developing methods for detecting fraud in the official statistics of a state's election returns. Among these efforts are those that employ Benford's Law, with the most common application being an attempt to proclaim some election or another fraud free or replete with fraud. This essay, however, argues that, despite its apparent utility in looking at other phenomena, Benford's Law is problematical at best as a forensic tool when applied to elections. Looking at simulations designed to model both fair and fraudulent contests as well as data drawn from elections we know, on the basis of other investigations, were either permeated by fraud or unlikely to have experienced any measurable malfeasance, we find that conformity with and deviations from Benford's Law follow no pattern. It is not simply that the Law occasionally judges a fraudulent election fair or a fair election fraudulent. Its “success rate” either way is essentially equivalent to a toss of a coin, thereby rendering it problematical at best as a forensic tool and wholly misleading at worst.

Type
Research Article
Copyright
Copyright © The Author 2011. Published by Oxford University Press on behalf of the Society for Political Methodology 

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