Periodic Reporting for period 4 - FASDEM (Failing and Successful Sequences of Democratization)
Okres sprawozdawczy: 2021-09-01 do 2023-02-28
The FASDEM project sought to address the shortcomings of the existing analyses of democratization - and then came to cover autocratization as well given the developments in the world - with a clear focus on endogenous processes that we can now investigate systematically for the first time. The objective was to answer two questions: Which are the failing versus successful sequences of democratization? What are the determining causal relationships in these sequences?
Critical for the project was the (then) new Varieties of Democracy (V-Dem) dataset. FASDEM PI Staffan I. Lindberg is one of four PIs for the V-Dem project and Director of the V-Dem Institute. The V-Dem dataset includes 600 indicators, 60+ component-indices, and five main indices of varieties of democracy from 1900 to the present – currently about 31 million data on democracy (Coppedge et al. 2023). Using this resource, FASDEM sought to contribute to how our understanding of the failing trajectories of democracy.
FASDEM offered an opportunity to test extant theories of failing and successful sequences of democratization and autocratization in the most rigorous fashion possible with a new set of methodologies and offer new knowledge with both academic and direct policy relevance. During the course of the program, it became obvious that current challenges in the world were entering around the issue of autocratization rather than democratization. In effect, the research agenda was adapted to include this area of research as well, and increasingly came to focus on issues around autocratization in the last part of the project.
Critical for the project was the (then) new Varieties of Democracy (V-Dem) dataset. FASDEM PI Staffan I. Lindberg is one of four PIs for the V-Dem project and Director of the V-Dem Institute. The V-Dem dataset includes 600 indicators, 60+ component-indices, and five main indices of varieties of democracy from 1900 to the present – currently about 31 million data on democracy (Coppedge et al. 2023). Using this resource, FASDEM sought to contribute to how our understanding of the failing trajectories of democracy.
FASDEM offered an opportunity to test extant theories of failing and successful sequences of democratization and autocratization in the most rigorous fashion possible with a new set of methodologies and offer new knowledge with both academic and direct policy relevance. During the course of the program, it became obvious that current challenges in the world were entering around the issue of autocratization rather than democratization. In effect, the research agenda was adapted to include this area of research as well, and increasingly came to focus on issues around autocratization in the last part of the project.
FASDEM has generated 29 articles in peer-reviewed journals and 3 pieces in working paper series that are still under review, and contributed to two volumes on Cambridge University Press (not listed since they are not open access and cannot be with CUP). FASDEM resulted among other things in a new, unique dataset: The episodes of Regime Transformation Dataset, freely available online. FASDEM also contributed to the later series of annual V-Dem datasets, a number of policy briefs aiming at the policy-practitioners' community, as well as a series of democracy and other reports (not listed in the "publications" but available at https://www.v-dem.net/publications/).
In the first subproject of FASDEM "Investigating Sequences in Ordinal Data: A New Approach With Adapted Evolutionary Models", and "Sequential Requisites Analysis: A New Method for Analyzing Sequential Relationships in Ordinal Data*" laid the ground with new methods used for sequence analysis. The article "Regimes of the World (RoW): Opening New Avenues..." added an important new typology for styling transitions, and "A third wave of autocratization is here: what is new about it?" advanced the concept of "episodes" and the first take on how to measure them", developed eventually to its final method through the article "Episodes of Regime Transformation" that is coming out in 2023. A simplified metric developed for policy-practitioners' is used for the State of the World articles (2017-2023) that was part of FASDEM's efforts at descriptively capture developments in the world.
Several pieces use these methods to describe sequences in episodes, among them, "The Accountability Sequence" for example indicates that most aspects of de-facto vertical account- ability precede other forms of accountability. Effective institutions of horizontal accountability—such as vigorous parliaments and independent high courts—evolve rather late in the sequence and build on progress in many other areas. “Institutionalizing Electoral Uncertainty and Authoritarian Regime Survival" we investigate the effects of sequences of multiparty elections on patterns of regime survival and failure in 262 authoritarian regimes from 1946 to 2010 and find that the institutionalisation of electoral uncertainty enhances authoritarian regime survival. In "How democracies prevail: democratic resilience as a two-stage process" we find that once autocratization begins, only one in five democracies manage to avert breakdown but also find 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.
Finally, we have broken new ground developing a really advanced prediction ensemble-model and developed an online dashboard tool showing the predictions of "adverse regime change" (https://v-dem.net/analysis). We have also presented at many academic conferences, and been called upon to present and give input to many policy/practitioners organizations and civil society.
In the first subproject of FASDEM "Investigating Sequences in Ordinal Data: A New Approach With Adapted Evolutionary Models", and "Sequential Requisites Analysis: A New Method for Analyzing Sequential Relationships in Ordinal Data*" laid the ground with new methods used for sequence analysis. The article "Regimes of the World (RoW): Opening New Avenues..." added an important new typology for styling transitions, and "A third wave of autocratization is here: what is new about it?" advanced the concept of "episodes" and the first take on how to measure them", developed eventually to its final method through the article "Episodes of Regime Transformation" that is coming out in 2023. A simplified metric developed for policy-practitioners' is used for the State of the World articles (2017-2023) that was part of FASDEM's efforts at descriptively capture developments in the world.
Several pieces use these methods to describe sequences in episodes, among them, "The Accountability Sequence" for example indicates that most aspects of de-facto vertical account- ability precede other forms of accountability. Effective institutions of horizontal accountability—such as vigorous parliaments and independent high courts—evolve rather late in the sequence and build on progress in many other areas. “Institutionalizing Electoral Uncertainty and Authoritarian Regime Survival" we investigate the effects of sequences of multiparty elections on patterns of regime survival and failure in 262 authoritarian regimes from 1946 to 2010 and find that the institutionalisation of electoral uncertainty enhances authoritarian regime survival. In "How democracies prevail: democratic resilience as a two-stage process" we find that once autocratization begins, only one in five democracies manage to avert breakdown but also find 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.
Finally, we have broken new ground developing a really advanced prediction ensemble-model and developed an online dashboard tool showing the predictions of "adverse regime change" (https://v-dem.net/analysis). We have also presented at many academic conferences, and been called upon to present and give input to many policy/practitioners organizations and civil society.
The methodological developments are taking us beyond the state of the art, and there have been several detailed, substantive results on distinct differences between sequences in successful episodes of democratization as well as autocratization and different types of failed episodes published - and some still in the works as working paper in the V-Dem series and currently under review. These results are already being used by a wide policy/practitioners community.
The pathbreaking "A third wave of autocratization is here" has been downloaded over 115,000 times and is already cited over 850 times in the literature. Among other things, we demonstrate there that a third wave of autocratization is indeed unfolding. It mainly affects democracies with gradual setbacks under a legal façade. A few other articles look at details, e.g. "The Institutional Order of Liberalization" reveal a clear pattern of reform during liberalization episodes with strong similarities across outcomes, but also that reforms to the administration of elections tend to develop comparatively earlier in episodes that produce a democratic transition; "Episodes of liberalization in autocracies" providing 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.
In the second subproject seeking to advance methods for causal inference using observational data, some breaking-through articles include "How to Make Causal Inferences with Time-Series Cross-Sectional Data under Selection on Observables" and "Generalized Nonlinear Difference-in-Difference-in-Differences": Difference-in-difference-in-differences (DiDiD) allow for the correction of unmeasured con-founding and function as a robustness check for difference-in-differences (DiD) techniques. Athey and Imbens (2006) provides a scale invariant, nonlinear DiD approach known as Changes-in-Changes (CiC). Sofer et al. (2016) extends CiC by showing that pre-treatment outcome measures are a special case of placebo (negative) outcomes and proposes a generalization of CiC called Negative Outcome Control (NOC). We develop a generalized nonlinear DiDiD approach we call NOCNOC that can be used either in the traditional DiDiD setting or when a placebo outcome is available in the pre and post-treatment data. We show that NOCNOC can correct for bias in Di-DiD, CiC, and NOC.
The pathbreaking "A third wave of autocratization is here" has been downloaded over 115,000 times and is already cited over 850 times in the literature. Among other things, we demonstrate there that a third wave of autocratization is indeed unfolding. It mainly affects democracies with gradual setbacks under a legal façade. A few other articles look at details, e.g. "The Institutional Order of Liberalization" reveal a clear pattern of reform during liberalization episodes with strong similarities across outcomes, but also that reforms to the administration of elections tend to develop comparatively earlier in episodes that produce a democratic transition; "Episodes of liberalization in autocracies" providing 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.
In the second subproject seeking to advance methods for causal inference using observational data, some breaking-through articles include "How to Make Causal Inferences with Time-Series Cross-Sectional Data under Selection on Observables" and "Generalized Nonlinear Difference-in-Difference-in-Differences": Difference-in-difference-in-differences (DiDiD) allow for the correction of unmeasured con-founding and function as a robustness check for difference-in-differences (DiD) techniques. Athey and Imbens (2006) provides a scale invariant, nonlinear DiD approach known as Changes-in-Changes (CiC). Sofer et al. (2016) extends CiC by showing that pre-treatment outcome measures are a special case of placebo (negative) outcomes and proposes a generalization of CiC called Negative Outcome Control (NOC). We develop a generalized nonlinear DiDiD approach we call NOCNOC that can be used either in the traditional DiDiD setting or when a placebo outcome is available in the pre and post-treatment data. We show that NOCNOC can correct for bias in Di-DiD, CiC, and NOC.