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Paper

Detection of Multinomial Voting Irregularities Mebane, Walter R. Sekhon, Jasjeet Wand, Jonathan Uploaded 07-17-2001 Keywords outlier detection robust estimation overdispersed multinomial generalized linear model 2000 presidential election voting irregularities Abstract We develop a robust estimator for an overdispersed multinomial regression model that we use to detect vote count outliers in the 2000 presidential election. The count vector we model contains vote totals for five candidate categories: Buchanan, Bush, Gore, Nader and ``other.'' We estimate the multinomial model using county-level data from Florida. In Florida, the model produces results for Buchanan that are essentially the same as in a binomial model: Palm Beach County has the largest positive residual for Buchanan. The multinomial model shows additional large discrepancies that almost always hurt Gore or Nader and help Bush or Buchanan.