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A Framework for Understanding Regime Transformation: Introducing the ERT Dataset

Sammanfattning
Gradual processes of democratization and autocratization have gained increased attention in the literature. Assessing such processes in a comparative framework remains a challenge, however, due to their under-conceptualization and a bifurcation of the democracy and autocracy literatures. This article provides a new conceptualization of regime transformation as substantial and sustained changes in democratic institutions and practices in either direction. This allows for studies to address both democratization and autocratization as related obverse processes. Using this framework, the article introduces a dataset that captures 680 unique episodes of regime transformation (ERT) from 1900 to 2019. These data provide novel insights into regime change over the past 120 years, illustrating the value of developing a unified framework for studying regime transformation. Such transformations, while meaningfully altering the qualities of the regime, only produce a regime transition about 32% of the time. The majority of episodes either end before a transition takes place or do not have the potential for such a transition (i.e. constituted further democratization in democratic regimes or further autocratization in autocratic regimes). The article also provides comparisons to existing datasets and illustrative case studies for face validity. It concludes with a discussion about how the ERT framework can be applied in peace research.
Länk till verkets webbplats
https://www.v-dem.net/media/filer_public/6f/29/6f29de7b-4c35-4089-859f-ed1b97f46c6b/wp113.pdf
Utgivare
V-Dem Institute
URL:
http://hdl.handle.net/2077/67595
Samlingar
  • Working Papers/Books /Department of Political Science / Statsvetenskapliga institutionen
Fil(er)
gupea_2077_67595_3.pdf (2.247Mb)
Datum
2021-02
Författare
Maerz, Seraphine F.
Edgell, Amanda B.
Wilson, Matthew C.
Hellmeier, Sebastian
Lindberg, Staffan I.
Serie/rapportnr.
Working Papers
2021:113
Språk
eng
Metadata
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