Statistical detection of systematic election irregularities

Klimek, P., Yegorov, Y., Hanel, R., & Thurner, S. (2012). Statistical detection of systematic election irregularities. Proceedings of the National Academy of Sciences 109 (41) 16469-16473. 10.1073/pnas.1210722109.

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Democratic societies are built around the principle of free and fair elections, and that each citizen's vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their references. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons.

Item Type: Article
Uncontrolled Keywords: Democratic decision making; Electoral district data; Statistical model; Voter turnout
Research Programs: Advanced Systems Analysis (ASA)
Bibliographic Reference: PNAS; 109(41):16469-16473 (9 October 2012) (Published online 24 September 2012)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 08:46
Last Modified: 27 Aug 2021 17:39

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