Title: "The Essays on Election Fraud in Authoritarian Regimes"

My dissertation is focused on the exploration of methodological and theoretical aspects of the statistical detection of election fraud, as well as the development and testing of theories designed to facilitate our understanding of election fraud and its origin in an authoritarian regimes. It revolves around three major research questions: Can the finite mixture model's estimates be validated against alternative data sources used to identify electoral anomalies and determine the magnitude of election frauds?, How do specific patterns in electoral data related to election fraud enable autocrats to identify and reward their most loyal subnational agents? and What is the general mechanism behind a close match between polls and rigged election results in autocracies? It fills this analytic gap by offering two formal models to explain the mechanisms by which autocrats, local agents, and survey organizations act in the context of the informational uncertainties generated by authoritarian regimes. The formal models help to clarify my core assumptions, build internally consistent theories, and derive valid hypotheses.

My first chapter explores whether election fraud precinct-level estimates obtained from a finite mixture likelihood model, recently developed by Mebane(2016), can be validated against alternative, more intuitive measures of election fraud. In this chapter the estimated precinct-level probabilities from the parametric model of election fraud are compared against measures based on election observation, different voting modes as well as several forensics indicators. This study also tests how well the new measure matches our theoretical expectations regarding geographic distribution of election fraud. Here I utilize propensity score matching, correlation analysis, and election forensics cluster detection methods. My entire analysis is built on the data from the 2011-2012 Russian federal elections.

My second chapter focuses on the exploration of how political loyalty of subnational agents can be associated with election fraud. It introduces a novel theoretical approach towards understanding election fraud under autocracies by suggesting a signaling model of election fraud and testing its basic implications on unique datasets from Russian and cross-national settings. According to the theory, the heads of subnational units can send their signals about loyalty to the leader by means of fraudulently augmented turnout or incumbent's vote percentages. In return, the local agents are rewarded by the leader with the larger amounts of postelectoral fiscal transfers. Basic implications from the formal model are supported by empirical data analysis of the Russian and cross-national data.

My third chapter explores whether election fraud can be conducive to the enhancement of electoral credibility in electoral autocracies. It provides an innovative perspective on the mechanism by which the autocrats in electoral autocracies strategically benefit from preference falsification, which boosts their own electoral ratings and encourages perpetration of election fraud. This chapter extends Kuran(1991)'s model by adding to the model the concept of election fraud. Theoretical implications of the model are tested on the original survey data collected by the author in Spring 2012 during the Russian presidential campaign, as well as original cross-national data including 59 countries. My theory is supported by empirical findings.

A practical consequence that follows from this dissertation is that the theories and methods presented here can enhance our understanding of election fraud in autocracies and contribute to the development of the empirical applications, such as Election Forensics Toolkit.

Download dissertation