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Comment on “Benford's Law and the Detection of Election Fraud”

Published online by Cambridge University Press:  04 January 2017

Walter R. Mebane Jr.
Walter R. Mebane Jr.*
Affiliation:
Departments of Political Science and Statistics, University of Michigan, 7735 Haven Hall, 505 South State Street, Ann Arbor, MI 48109-1045. e-mail: wmebane@umich.edu
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Abstract

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“Benford's Law and the Detection of Election Fraud” raises doubts about whether a test based on the mean of the second significant digit of vote counts equals 4.187 is useful as a test for the occurrence of election fraud. The paper mistakenly associates such a test with Benford's Law, considers a simulation exercise that has no apparent relevance for any actual election, applies the test to inappropriate levels of aggregation, and ignores existing analysis of recent elections in Russia. If tests based on the second significant digit of precinct-level vote counts are diagnostic of election fraud, the tests need to use expectations that take into account the features of ordinary elections, such as strategic actions. Whether the tests are useful for detecting fraud remains an open question, but approaching this question requires an approach more nuanced and tied to careful analysis of real election data than one sees in the discussed paper.

Type
Research Article
Information
Political Analysis , Volume 19 , Issue 3 , Summer 2011 , pp. 269 - 272
Copyright
Copyright © The Author 2011. Published by Oxford University Press on behalf of the Society for Political Methodology 

References

Alesina, Alberto, and Rosenthal, Howard. 1995. Partisan politics, divided government, and the economy. New York, NY: Cambridge University Press.Google Scholar
Berger, Arno. 2005. Multi-dimensional dynamical systems and Benford's Law. Discrete and Continuous Dynamical Systems 13: 219–37.Google Scholar
Brady, Henry E. 2005. Comments on Benford's Law and the Venezuelan election Working paper, January 19, 2005.Google Scholar
Cox, Gary W. 1994. Strategic voting equilibria under the single nontransferable vote. American Political Science Review 88: 608–21.Google Scholar
Deckert, Joseph, Myagkov, Mikhail, and Ordeshook, Peter C. 2011. Benford's Law and the detection of election fraud. Political Analysis 19(3): 245–68.Google Scholar
Grendar, Marian, Judge, George, and Schechter, Laura. 2007. An empirical non-parametric likelihood family of data-based Benford-like distributions. Physica A 380: 429–38.Google Scholar
Kalinin, Kirill, and Mebane, Walter R. Jr. 2011. Understanding electoral frauds through evolution of Russian federalism: From ‘Bargaining Loyalty’ to ‘Signaling Loyalty’. Paper prepared for the 2011 Annual Meeting of the Midwest Political Science Association, Chicago, IL, March 31-April 2.Google Scholar
Mebane, Walter R. Jr. 2006. Election forensics: Vote counts and Benford's law. Paper prepared for the 2006 Summer Meeting of the Political Methodology Society, UC-Davis, Davis, CA, July 20-22.Google Scholar
Mebane, Walter R. Jr. 2007. Statistics for digits. Paper presented at the 2007 Summer Meeting of the Political Methodology Society, Pennsylvania State University, State College, PA, July 18-21.Google Scholar
Mebane, Walter R. Jr. 2008. Election forensics: The second-digit Benford's law test and recent American presidential elections. In Election Fraud: Detecting and Deterring Electoral Manipulation, ed. Michael Alvarez, R., Hall, Thad E., and Hyde, Susan D. Washington, DC: Brookings Institution.Google Scholar
Mebane, Walter R. Jr. 2010a. Election fraud or strategic voting? Paper prepared for the 2010 Annual Meeting of the Midwest Political Science Association, Chicago, IL, April 22-25.Google Scholar
Mebane, Walter R. Jr. 2010b. Election fraud or strategic voting? Can second-digit tests tell the difference? Paper prepared for the 2010 Summer Meeting of the Political Methodology Society, University of Iowa, Iowa City, IA, July 22-24.Google Scholar
Mebane, Walter R. Jr. 2010c. Fraud in the 2009 presidential election in Iran? Chance 23: 6–15.Google Scholar
Mebane, Walter R. Jr., and Kalinin, Kirill. 2009a. Comparative election fraud detection. Paper prepared for the 2009 Annual Meeting of the Midwest Political Science Association, Chicago, IL, April 2-5.Google Scholar
Mebane, Walter R. Jr., and Kalinin, Kirill. 2009b. Electoral falsification in Russia: Complex diagnostics selections 2003-2004, 2007-2008 (in Russian). Electoral Policy REO 2/09: 57–70.Google Scholar
Mebane, Walter R. Jr., and Kalinin, Kirill. 2010. Electoral fraud in Russia: Vote counts analysis using second-digit mean tests. Paper prepared for the 2010 Annual Meeting of the Midwest Political Science Association, Chicago, IL, April 22-25.Google Scholar
Myagkov, Mikhail, Ordeshook, Peter C., and Shaikin, Dimitry. 2009. The forensics of election fraud: With applications to Russia and Ukraine. New York, NY: Cambridge University Press.Google Scholar
Rodriguez, Ricardo J. 2004. First significant digit patterns from mixtures of uniform distributions. American Statistician 58: 64–71.Google Scholar