Open Access Journal

ISSN: 2183-2463

Article | Open Access

Identifying Profiles of Democracies: A Cluster Analysis Based on the Democracy Matrix Dataset from 1900 to 2017

Full Text   PDF (free download)
Views: 2715 | Downloads: 1492


Abstract:  This study examines types of democracies that result from trade-offs within the democratic quality. Recently, the existence and relevance of trade-offs has been widely discussed. The idea is that the functions associated with the quality of democracy cannot all be maximized simultaneously. Thus, trade-offs are expressed in distinct profiles of democracy. Different profiles of democracy favour certain democracy dimensions over others due to their institutional design. Conceptually, we differentiate between four different democracy profiles: a libertarian-majoritarian (high political freedom, lower political equality, and lower political and legal control values), an egalitarian-majoritarian (high equality combined with lower freedom and control values), as well as two control-focused democracy profiles (high control values either with high degrees of freedom or high degrees of equality). We apply a cluster analysis with a focus on cluster validation on the Democracy Matrix dataset—a customized version of the Varieties-of-Democracy dataset. To increase the robustness of the cluster results, this study uses several different cluster algorithms, multiple fit indices as well as data resampling techniques. Based on all democracies between 1900 and 2017, we find strong empirical evidence for these democracy profiles. Finally, we discuss the temporal development and spatial distribution of the democracy profiles globally across the three waves of democracy, as well as for individual countries.

Keywords:  cluster analysis; democracy; democracy profiles; quality of democracy; trade-offs

Published:  


Supplementary Files:

DOI: https://doi.org/10.17645/pag.v7i4.2244


© Oliver Schlenkrich. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.