Using Vote Counts' Digits to Diagnose Strategies and Frauds: Russia

61 Pages Posted: 12 Aug 2013

See all articles by Walter R. Mebane

Walter R. Mebane

University of Michigan at Ann Arbor - Department of Political Science

Date Written: 2013

Abstract

Tests of the digits of vote counts have been proposed to diagnose election fraud. Both the second-digit Benford's-like Law (2BL) and the idea that the last digits should be uniformly distributed have been proposed as standards for clean elections. Many claim that election fraud is rampant in recent Russian federal elections (since 2004), so Russia should be a good setting in which to see whether the digit tests add any diagnostic power. Using precinct-level data from Russia, I first use a randomization test to identify sets of precincts (called UIKs in Russia) in which vote counts for candidates are augmented compared to vote counts in a comparison sets of UIKs. These are a subset of UIKs in which turnout percentages or the percentage of votes for Putin (or United Russia) are divisible by five. Then I run tests of the second and last digits of the UIK vote counts both for the entire set of UIKs in an election year and separately for various sets of UIKs. The digit tests produce surprising and on balance implausible results. For example, they suggest that none of the votes for Putin in 2004 and 2012 or for United Russia in 2011 were fraudulent, while votes for Medvedev in 2008 were fraudulent. The usefulness of simple and direct application of either kind of digit tests for fraud detection seems questionable, although in connection with more nuanced interpretations they may be useful.

Keywords: election forensics, digit tests, randomization inference, Russian elections

JEL Classification: C00

Suggested Citation

Mebane, Walter R., Using Vote Counts' Digits to Diagnose Strategies and Frauds: Russia (2013). APSA 2013 Annual Meeting Paper; American Political Science Association 2013 Annual Meeting. Available at SSRN: https://ssrn.com/abstract=2303480

Walter R. Mebane (Contact Author)

University of Michigan at Ann Arbor - Department of Political Science ( email )

Ann Arbor, MI 48109
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
47
Abstract Views
306
PlumX Metrics