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AbstractWhen authoritarian regimes liberalize, are there observable patterns in the ordering of reforms, and are these patterns distinct for cases that transition to democracy? While the prevailing literature tends to focus on exogenous 'determinants' of democracy, this letter describes the endogenous dynamics of liberalization itself. Using pairwise domination analysis, it assesses the institutional order of reforms during 371 episodes of liberalization in autocracies between 1900 and 2019. Based on twenty-four indicators of democratic institutions and practices, our findings reveal (1) a clear pattern of reform during liberalization episodes, (2) with strong similarities across outcomes, but also that (3) reforms to the administration of elections tend to develop comparatively earlier in episodes of liberalization that produce a democratic transition.

This article introduces a novel conceptualization of democratic resilience - a two-stage process where democracies avoid democratic declines altogether or avert democratic breakdown given that such autocratization is ongoing. Drawing on the Episodes of Regime Transformation (ERT) dataset, we find that democracies have had a high level of resilience to onset of autocratization since 1900. Nevertheless, democratic resilience has become substantially weaker since the end of the Cold War. Fifty-nine episodes of sustained and substantial declines in democratic practices have occurred since 1993, leading to the unprecedented breakdown of 36 democratic regimes. Ominously, we find that once autocratization begins, only one in five democracies manage to avert breakdown. We also analyse which factors are associated with each stage of democratic resilience. The results suggest that democracies are more resilient when strong judicial constraints on the executive are present and democratic institutions were strong in the past. Conversely and adding nuance to the literature, economic development is only associated with resilience to onset of autocratization, not to resilience against breakdown once autocratization has begun.

This article provides a new conceptualization of regime transformation that allows scholars to address democratization and autocratization as related but obverse processes. We introduce a dataset that captures 680 episodes of regime transformation (ERT) from 1900 to 2019 and offers novel insights into regime change over the past 120 years. The ERT has three main advantages over other approaches. First, it avoids problematic assumptions of unit homogeneity and constant as well as symmetric effects. Second, it integrates key insights from qualitative studies by treating regime change as a gradual and uncertain process. Third, the ERT is based on a unified framework for studying regime transformation in either direction. The dataset differentiates between four broad types of regime transformation: liberalization in autocracies, democratic deepening in democracies, and autocratization in both democracies and autocracies (democratic and autocratic regression). It further distinguishes ten patterns with distinct outcomes, including standard depictions of regime change (i.e. democratic transition or breakdown). A minority (32%) of ERTs produce a regime transition, with the majority of episodes either ending before a transition takes place or not having the potential for such a transition (i.e. further democratization in democratic regimes or further autocratization in autocratic regimes). We also provide comparisons to other datasets, illustrative case studies to demonstrate face validity, and a discussion about how the ERT framework can be applied in peace research.

AbstractThis paper introduces a new approach to the quantitative study of democratization. Building on the comparative case-study and large-N literature, it outlines an episode approach that identifies the discrete beginning of a period of political liberalization, traces its progression, and classifies episodes as successful versus different types of failing outcomes, thus avoiding potentially fallacious assumptions of unit homogeneity. We provide a description and analysis of all 383 liberalization episodes from 1900 to 2019, offering new insights on democratic "waves". We also demonstrate the value of this approach by showing that while several established covariates are valuable for predicting the ultimate outcomes, none explain the onset of a period of liberalization.

This paper introduces a new approach to the quantitative study of democratization. Building on the comparative case-study and large-N literature, it outlines an episode approach that identifies the discrete beginning of a period of political liberalization, traces its progression, and classifies episodes as successful versus different types of failing outcomes, thus avoiding potentially fallacious assumptions of unit homogeneity. We provide a description and analysis of all 383 liberalization episodes from 1900 to 2019, offering new insights on democratic "waves". We also demonstrate the value of this approach by showing that while several established covariates are valuable for predicting the ultimate outcomes, none explain the onset of a period of liberalization.

During the past decade, analyses drawing on several democracy measures have shown a global trend of democratic retrenchment. While these democracy measures use radically different methodologies, most partially or fully rely on subjective judgments to produce estimates of the level of democracy within states. Such projects continuously grapple with balancing conceptual coverage with the potential for bias (Munck and Verkuilen 2002; Przeworski et al. 2000). Little and Meng (L&M) (2023) reintroduce this debate, arguing that "objective" measures of democracy show little evidence of recent global democratic backsliding.1 By extension, they posit that time-varying expert bias drives the appearance of democratic retrenchment in measures that incorporate expert judgments. In this article, we engage with (1) broader debates on democracy measurement and democratic backsliding, and (2) L&M's specific data and conclusions.