Sometimes the normal course of events is disrupted by a particularly swift and profound change. Historians have often referred to such changes as revolutions, and, though they have identified many of them, they have rarely supported their claims with statistical evidence. Here, we present a method to identify revolutions based on a measure of multivariate rate of change called Foote novelty. We define revolutions as those periods of time when the value of this measure is, by a non-parametric test, shown to significantly exceed the background rate. Our method also identifies conservative periods when the rate of change is unusually low. We apply it to several quantitative data sets that capture long-term political, social and cultural changes and, in some of them, identify revolutions - both well known and not. Our method is general and can be applied to any phenomenon captured by multivariate time series data of sufficient quality.
This paper presents a new approach for studying temporal sequences across ordinal variables. It involves three complementary approaches (frequency tables, transitional graphs, and dependency tables), as well as an established adaptation based on Bayesian dynamical systems, inferring a general system of change. The frequency tables count pairs of values in two variables and transitional graphs depict changes, showing which variable tends to attain high values first. The dependency tables investigate which values of one variable are prerequisites for values in another, as a more direct test of causal hypotheses. We illustrate the proposed approaches by analyzing the V-Dem dataset, and show that changes in electoral democracy are preceded by changes in freedom of expression and access to alternative information.
This paper presents a new method inspired by evolutionary biology for analyzing longer sequences of requisites for the emergence of particular outcome variables across numerous combinations of ordinal variables in social science analysis. The approach involves repeated pairwise investigations of states in a set of variables and identifying what states in the variables that occur before states in all other variables. We illustrate the proposed method by analyzing a set of variables from version 6 of the V-Dem dataset (Coppedge et al. 2015a, b). With a large set of indicators measured over many years, the method makes it possible to explore long, complex sequences across many variables in quantitative datasets. This affords an opportunity, for example, to disentangle the sequential requisites of failing and successful sequences in democratization. For policy purposes this is instrumental: Which components of democracy are most exogenous and least endogenous and therefore the ideal targets for democracy promotion at different stages?
What determines countries’ successful transition to democracy? This article explores the impact of granting civil rights in authoritarian regimes and especially the gendered aspect of this process. It argues that both men's and women's liberal rights are essential conditions for democratisation to take place: providing both women and men rights reduces an inequality that affects half of the population, thus increasing the costs of repression and enabling the formation of women's organising – historically important to spark protests in initial phases of democratisation. This argument is tested empirically using data that cover 173 countries over the years 1900–2012 and contain more nuanced measures than commonly used. Through novel sequence analysis methods, the results suggest that in order to gain electoral democracy a country first needs to furnish civil liberties to both women and men.