dc.description.abstract | Classifying political regimes has never been as difficult as in this day and age. Most regimes in the world now hold de-jure multiparty elections with universal suffrage. Yet, in some countries these elections ensure that political rulers are – at least somewhat – accountable to the electorate whereas in others they are a mere window dressing exercise for authoritarian politics. Hence, regime types need to be distinguished based on the de-facto implementation of democratic rules. To this end, researchers increasingly turn to expert-coded data sets such as the new Varieties of Democracy (V-Dem) dataset. Using V-Dem data, we propose an operationalization of four important regime types – closed and electoral autocracies; electoral and liberal democracies – with vast coverage (almost all countries form 1900 to 2016) and precision. Our new Regimes in the World (RIW) measure includes uncertainty estimates to identify countries in the grey zone between regime types and account for inter-coder disagreement. In cases of disagreement with other datasets (7-12% of the cases), we classify regimes with severe electoral manipulation and infringements of the political freedoms more frequently as electoral autocracies than other datasets, which suggests that our measure captures the opaqueness of contemporary autocracies better. | sv |
dc.description.sponsorship | For helpful comments, we thank Philip Keefer, Beth Simmons, Valeriya Mechkova and participants of the 2017 V-Dem Research Conference, where an earlier version of this paper was discussed. This research project was supported by Riksbankens Jubileumsfond, Grant M13-0559:1, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; by Knut and Alice Wallenberg Foundation to Wallenberg Academy Fellow Staffan I. Lindberg, Grant 2013.0166, V-Dem Institute, University of Gothenburg, Sweden; by European Research Council, Grant 724191, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; as well as by internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg. We performed simulations and other computational tasks using resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Center in Sweden, SNIC 2016/1-382 and 2017/1-68. We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber at SNIC in facilitating our use of their respective systems. | sv |