Detecting Election Fraud from Irregularities in Vote-Share Distributions. (22nd February 2017)

• Record Type: Journal Article
• Authors: Rozenas, Arturas
• Is Part Of: Political analysis. Volume 25:Number 1(2017)
• Page Start: 41
• Page End: 56
• Publication Date: 2017-02-22
• Subjects: Political science -- Methodology -- Periodicals; Electronic journals; 320.011
• DOI: 10.1017/pan.2016.9
• Languages: English
• ISSNs: 1047-1987

Abstract

Abstract : I develop a novel method to detect election fraud from irregular patterns in the distribution of vote-shares. I build on a widely discussed observation that in some elections where fraud allegations abound, suspiciously many polling stations return coarse vote-shares (e.g., 0.50, 0.60, 0.75) for the ruling party, which seems highly implausible in large electorates. Using analytical results and simulations, I show that sheer frequency of such coarse vote-shares is entirely plausible due to simple numeric laws and does not by itself constitute evidence of fraud. To avoid false positive errors in fraud detection, I propose a resampled kernel density method (RKD) to measure whether the coarse vote-shares occur too frequently to raise a statistically qualified suspicion of fraud. I illustrate the method on election data from Russia and Canada as well as simulated data. A software package is provided for an easy implementation of the method.