Monarchy was the dominant form of rule in the pre-modern era and it persists in a handful of countries. We propose a unified theoretical explanation for its rise and decline. Specifically, we argue that monarchy offers an efficient solution to the primordial problem of order where societies are large and citizens isolated from each other and hence have difficulty coordinating. Its efficiency is challenged by other methods of leadership selection when communication costs decline, lowering barriers to citizen coordination. This explains its dominance in the pre-modern world and its subsequent demise. To test this theory, we produce an original dataset that codes monarchies and republics in Europe (back to 1100) and the world (back to 1700). With this dataset, we test a number of observable implications of the theory—centering on territory size, political stability, tenure in office, conflict, and the role of mass communications in the modern era.

Parties spend parts of their campaigns criticizing other parties’ performance and characteristics, such as honesty, integrity, and unity. These attacks aim to negatively affect the target parties’ electoral performance. But do they work? While attacks are informative, we argue that how voters react to negative campaigning depends on their partisanship. While the target’s copartisans are more likely to get mobilized in favor of their party, the attacker’s copartisans are expected to punish the target due to their respective partisan motivations. We expect null effects for attacks for partisans of third parties as well as nonpartisans. Combining a new dataset on campaign rhetoric with survey data from eight European countries, we show support for most but not all of our expectations. These results have important implications for the electoral campaigns literature.

Most crossnational indices of democracy rely centrally on coder judgments, which are susceptible to personal bias and error, and also require expensive and time-consuming coding by experts. The few measures based exclusively on observable indicators are either dichotomous or rely on a few rather crude proxies. This project lays out an approach to measurement based on observables that aims to preserve the nuanced quality of subjectively coded democracy indices. First, we gather data for a wide range of observable indicators, X´, that capture different aspects of the democratic process. Next, we use supervised random forest machine learning to predict Z using factual indicators, X´, creating an observable-to-subjective score mapping (OSM). The mapping that provides the best cross-validated fit to the outcome serves as an alternate index, Z´, for that conceptualization of democracy.Information loss from Z to Z´ is minimal for indices centered on an electoral conception of democracy and this loss may be advantageous for some purposes. It is free of idiosyncratic coder errors arising from misinformation, slack, or biases for or against a regime. It is also less susceptible to systematic bias that may arise from coders’ inferences about a country’s regime status, e.g., from the ideology of the current ruler. The data collection procedure and mode of analysis is fully transparent and replicable, and the procedure is cheap to produce, easy to update, and offers coverage for all polities with sovereign or semisovereign status, surpassing the sample of any existing index. We show that this expansive coverage makes a big difference to our understanding of some causal questions.

Multiple well-known democracy rating projects—including Freedom House, Polity,and V-Dem—have identified apparent global regression in recent years. These measures rely on partly subjective indicators, which could, in principle, suffer from rater bias. For instance, Little and Meng (2023) argue that shared beliefs driven by the current zeitgeist could lead to shared biases that produce the appearance of democratic backsliding in subjectively coded measures. To assess this argument, and the strength of the evidence for global democratic backsliding, we propose an observable-to-subjective score mapping (OSM) methodology that uses only easily observable features of democracy to predict existing indices of democracy. Applying this methodology to three prominent democracy indices, we find evidence of backsliding, but beginning later and not as pronounced as suggested by some of the original indices. Our approach suggests that particularly the Freedom House measure is out of track with the recent patterns in observable indicators and that there has been a stasis or, at most, a modest decline in the average level of democracy.

The study of electoral contestation generally focuses on districts or regions rather than polities.We present a new dataset that measures electoral contestation through historical records of elections in sovereign and semi-sovereign polities throughout the world from 1789 to the present.We also offer a new index of contestation intended to capture multiple dimensions of this complex concept. Our second objective is to explain variation across polities and through time in electoral contestation. We argue that the degree of contestation in a polity is affected by demography, with larger polities fostering greater electoral contestation. This hypothesis is tested with a series of cross-national regression tests that employ a variety of specifications and estimators -crosssectional, fixed-effect, and instrumental variable. We find a robust association between population and contestation extending throughout the modern era. 51 49 49 98 98 3. A (Ch) B (I)