Democracy is under threat globally from democratically elected leaders engaging in erosion of media freedom, civil society, and the rule of law. What distinguishes democracies that prevail against the forces of autocratization? This article breaks new ground by conceptualizing democratic resilience as a two-stage process, whereby democracies first exhibit resilience by avoiding autocratization altogether and second, by avoiding democratic breakdown given that autocratization has occurred. To model this two-stage process, we introduce the Episodes of Regime Transformation (ERT) dataset tracking autocratization since 1900. These data demonstrate the extraordinary nature of the current wave of autocratization: Fifty-nine (61%) episodes of democratic regression in the ERT began after 1992. Since then, autocratization episodes have killed an unprecedented 36 democratic regimes. Using a selection-model, we simultaneously test for factors that make democracies more prone to experience democratic regression and, given this, factors that explain democratic breakdown. Results from the explanatory analysis suggest that constraints on the executive are positively associated with a reduced risk of autocratization. Once autocratization is ongoing, we find that a long history of democratic institutions, durable judicial constraints on the executive, and more democratic neighbours are factors that make democracy more likely to prevail.We recognize support by the Swedish Research Council, Grant 2018-01614, PI: Anna Lührmann; by Knut
and Alice Wallenberg Foundation to Wallenberg Academy Fellow Staffan I. Lindberg, Grant 2018.0144; by European
Research Council, Grant 724191, PI: Staffan I. Lindberg; 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. The computations of expert data were enabled by the Swedish National Infrastructure for Computing
(SNIC) at National Supercomputer Centre, Linköping University, partially funded by the Swedish Research Council through grant agreement no. 2019/3-516
