Validating Precinct-Level Measures of Fraud: Evidence from the Russian Electoral Cycle 2011-2012

Abstract

This research is designed to explore whether election fraud precinct-level estimates obtained from a finite mixture likelihood model, recently developed by Mebane(2015), can be validated against alternative, more intuitive measures of election fraud. I estimate the precinct-level probabilities from the parametric model of election fraud and compare them against measures based on election observation, different voting modes as well as several popular forensics indicators. This study also tests how well the cluster patterns of the finite mixture likelihood probabilities on different levels of aggregation are associated with the clusters of alternative election fraud measures. The data used is from the parliamentary election 2011 and presidential election 2012 in Russia. My basic findings demonstrate that finite mixture estimates if compared to alternative sources of information, seem to be effectively capturing electoral anomalies, making this new estimator very useful in election forensics research.