Presidents and Assemblies: Constitutional Design and Electoral Dynamics

Rule of law.

Presidentialism and Democracy in Latin America

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.

How democracies prevail: democratic resilience as a two-stage process.

ABSTRACT Why do voters vote for undemocratic politicians in a democracy? My chief contention is that affective polarization has become a primary factor driving support for undemocratic politicians. Once partisan identification turns into a salient identity in the hierarchy of group affiliations, it has the potential to widen inter-party distances. Such a political environment fosters positive beliefs of their preferred party and negative beliefs of the other party, which promote political cynicism, intolerance and increase partisan loyalty. As a result, crossing party lines becomes costly, even when incumbents violate democratic principles or incumbents’ economic policies do not appeal to supporters’ interests. This tradeoff enables undemocratic politicians to evade electoral sanctions for undemocratic behaviour. I created an extended version of Reiljan’s affective polarization application. The new dataset covers affective polarization scores of 53 countries calculated over 170 national election surveys. I find that increasing affective polarization is highly correlated with democratic backsliding, less accountability, less freedom, fewer rights, and less deliberation in democracies. However, ideological polarization has shown no correlation.

The relationship between affective polarization and democratic backsliding: comparative evidence

/pdf/volatilidad-electoral-y-alternancia-politica-a-nivel-2abqdr2hlj.pdf

Volatilidad electoral y alternancia política a nivel subnacional en Uruguay, 2000-2015

Social Scientists and Biostatisticians often employ conventional parametric survival or mixture cure models (e.g., Weibull, Exponential) to analyze outcome variables in survival data that focus on the time until an event occurred or “failed” (Box-Steffensmeier & Zorn, 1999; Lee, Chakraborty, & Sun, 2017; Maller & Zhou, 1996). An important assumption underlying these models is that researchers record the date year, month or day in which an event or observation of interest failed (i.e., “terminated”) accurately. Yet events that are recorded as having failed at a given point in time can be inaccurately measured (Bagozzi, Joo, Kim, & Mukherjee, 2019; Clark, Bradburn, Love, & Altman, 2003; Schober & Vetter, 2018). Inaccurate measurement of this sort leads to a subset of misclassified failure cases in survival data in which some subjects are recorded as having failed or experienced the event of interest even though they in actuality “live on” past their recorded-failure point.

/pdf/bayesmfsurv-an-r-package-to-estimate-bayesian-split-5fn0pyq0c4.pdf

BayesMFSurv: An R Package to Estimate Bayesian Split-Population Survival Models With (and Without) Misclassified Failure Events

/pdf/bayesspsurv-an-r-package-to-estimate-bayesian-spatial-split-1wf87y10d4.pdf

BayesSPsurv: An R Package to Estimate Bayesian (Spatial) Split-Population Survival Models

Survival data often include an “immune” or cured fraction of units that will never experience an event and conversely, an “at risk” fraction that can fail or die. It is also plausible that spatial clustering (i.e., spatial autocorrelation) in latent or unmeasured risk factors among adjacent units can affect their odds of being immune and survival time of interest. To address these methodological challenges, this article introduces a class of parametric Spatial split-population survival models—also denoted as Spatial cure models—that explicitly accounts for the influence of spatial autocorrelation among the underlying risk propensities of units on not only their probability of being immune but also their risk of experiencing the event of interest. Our approach is Bayesian in that we account for spatial autocorrelation in unmeasured risk factors across adjacent units in the cure model’s split-stage (cure rate portion) and survival stage via the conditional autoregressive prior (CAR) prior. The article also presents a set of parametric split-population survival models with non-spatial i.i.d frailties and without frailties, and time-varying covariates can be included in all the models mentioned above. Bayesian inference of the non-spatial and spatial cure models is conducted via a hybrid Markov Chain Monte Carlo (MCMC) algorithm. The relevant full conditional distributions required for MCMC sampling are also derived and presented in the paper. We fit all the models to survival data on post-civil war peace to demonstrate their main applicability and main features.

Bayesian Spatial Split-Population Models for the Social Sciences

Does the executive's institutional hegemony represent a risk to the survival of democracy? By hegemony, we refer to the president's ability to control other institutions, particularly the legislatu...

Presidential hegemony and democratic backsliding in Latin America, 1925–2016

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