Election forensics is the field devoted to using statistical methods to determine whether the results of an election are accurate: whether the results are the collective choice implied by citizens' intentions given the election rules. The fundamental challenge for election forensics is that strategic behavior is a ubiquitous aspect of political activity, and both strategic behavior and frauds cause patterns in election results that may appear anomalous in statistical estimates and tests. I use data from elections in several countries to illustrate how several models used in election forensics—including digit tests and tests focused on the normality of turnout and vote proportions—do not correctly discriminate between strategic behavior and frauds. Confounds with strategies are apparent even when geographically weighted estimation and measures of postelection complaints are considered. Only one method has so far given clear signs that it does not confuse strategic behavior and frauds. Latent dimensions of frauds seem to underlie that method's estimates and postelection complaints.
The BIDS Data Science Lecture Series is co-hosted by BIDS and the Data, Science, and Inference Seminar.
Walter R. Mebane, Jr., is a professor of political science and a professor of statistics at the University of Michigan, Ann Arbor. He works on political methodology and American politics, especially elections. His current primary project is election forensics, which aims to develop statistical and computational tools for detecting anomalies and diagnosing fraud in election results. He is writing a book on this topic. He also has a grant from IIE/USAID to develop an election forensics toolkit. His work in this area includes, among others, papers about the 2000 presidential election, a report written for the Democratic National Committee analyzing the 2004 presidential election in Ohio, and analysis of election fraud in Russia and of likely fraud in the 2009 election in Iran.