Suchergebnisse

To understand the limitations of discrete regime type data for studying authoritarianism, I scrutinize three regime type data sets provided by Cheibub, Gandhi, and Vreeland, Hadenius and Teorell, and Geddes. The political narratives of Nicaragua, Colombia, and Brazil show that the different data sets on regime type lend themselves to concept stretching and misuse, which threatens measurement validity. In an extension of Fjelde's analysis of civil conflict onset, I demonstrate that interchangeably using the data sets leads to divergent predictions, it is sensitive to outliers, and the data ignore certain institutions. The critique expounds on special issues with discrete data on regime type so that scholars make more informed choices and are better able to compare results. The mixed-methods assessment of discrete data on regime type demonstrates the importance of proper concept formation in theory testing. Maximizing the impact of such data requires the scholar to make more theoretically informed choices. [Reprinted by permission of Sage Publications Inc., copyright holder.]

To understand the limitations of discrete regime type data for studying authoritarianism, I scrutinize three regime type data sets provided by Cheibub, Gandhi, and Vreeland, Hadenius and Teorell, and Geddes. The political narratives of Nicaragua, Colombia, and Brazil show that the different data sets on regime type lend themselves to concept stretching and misuse, which threatens measurement validity. In an extension of Fjelde's analysis of civil conflict onset, I demonstrate that interchangeably using the data sets leads to divergent predictions, it is sensitive to outliers, and the data ignore certain institutions. The critique expounds on special issues with discrete data on regime type so that scholars make more informed choices and are better able to compare results. The mixed-methods assessment of discrete data on regime type demonstrates the importance of proper concept formation in theory testing. Maximizing the impact of such data requires the scholar to make more theoretically informed choices.

Although empirical research has generally demonstrated that democracies experience more terrorism than autocracies, research suggests that this depends upon complex institutional differences that go beyond the democracy‐autocracy divide. This study examines these differences, linking institutions to strategies of coercion and co‐optation. Using zero‐inflated negative binomial regression estimations on Geddes' (2003) autocratic regime‐type data for 161 countries between 1970 and 2006, we find that single‐party authoritarian regimes consistently experience less domestic and international terrorism relative to military autocracies and democracies. This finding is robust to a large number of specifications, underscoring the explanatory power of regime type for predicting terrorism. Our explanation for these findings is that party‐based autocracies have a wider range of coercion and co‐option strategies that they can employ to address grievance and dissent than do other, more strategically restricted, regimes.

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.