Project Details
Critical Junctures and the Survival of Dictatorships: Explaining the Stability of Autocratic Regimes
Applicant
Professor Dr. Wolfgang Merkel
Subject Area
Political Science
Term
from 2011 to 2015
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 181040310
The ‘third wave of democratization’ left aside a considerable number of well-functioning autocracies. How has authoritarianism in an age of democratization been able to survive? We want to address three shortcomings in the literature: First, most of the studies rely on one-dimensional typologies, focusing on the structure of autocratic domination, but ignoring specific reproduction mechanisms of autocratic regimes. Second, studies juxtapose separate theoretical strands we seek to synthesize by linking structure and agency in an historical institutionalist approach. Third, little attention is paid to the genesis and development of institutions that bolster autocratic regimes. We want to focus on such institutions, specifically taking into account the time dimension of autocratic institutionalization. We identify three pillars of stability of autocratic rule: legitimacy, co-optation, and repression. We hypothesize that the institutionalization and balance of these pillars are responsible for autocratic stability. Referring to historical institutionalism’s key concept of critical juncture, we propose that regime-threatening critical junctures occur if the other two can no longer compensate a crisis in the remaining pillar. We apply a nested research design, combining large-N quantitative analysis with small-N qualitative case study. We construct a dataset of non-democratic regimes from 1972 to 2009. Based on our three-pillar model, we develop a typology of autocratic rule resting on different combinations of the three pillars. We then conduct a survival analysis, estimating the effect of the three pillars on the probability of regime breakdown. Finally, we conduct in-depth case studies of outlier cases that do not fit our theoretical and statistical models. The goal is to use qualitative studies to test and improve our theoretical model.
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