We are delighted to present one of the major contributions of our project – cross-regional data on electoral malpractice in Russia at the State Duma and Presidential elections 2007-2021. The data covers socioeconomic characteristics of Russian regions, as well as variables on TV and Internet coverage in each subject of the Russian Federation. The dataset contributes with the new variables on electoral coverage during both Presidential and State Duma electoral campaigns which capture the number of messages on elections in Russian regional media sources and the number of messages on electoral fraud. The dataset also encompasses electoral outcomes for political parties as well as basic socio-economic variables. Data covers four electoral cycles for the State Duma elections (2007, 2011, 2016, 2021) and three cycles for presidential elections (2008, 2012, 2018). More detailed variables on media coverage are to be added in the coming months. In this post, we visualize basic descriptive statistics on reporting electoral irregularities, their distribution across federal elections and regions as well as correlations with the main electoral variables: turnout, voting, and economic development. This post is written by Margarita Zavadskaya, Valeria Caras, and Elena Gorbacheva
Reporting fraud across federal elections: highest numbers in 2012
Most of the studies on how fraud is connected with political behaviour focus on election day or ex post violations, while we also include ex ante violations, i.e. malpractice that occurs on the eve of federal elections. Fraud rarely occurs spontaneously under autocracies and usually, implementation of fraud requires certain preparations in terms of amending the legal framework, excluding and suppressing opposition candidates and parties well before the election day. Since the direct measure of violations is even more challenging compared to detecting fraud on election day, we rely on media data that contain any mention of electoral malpractice during the election campaign. Our data allow one to take a first glance at the joint distributions and draw preliminary conclusions.