Suchergebnisse

How does the passage of time contribute to the establishment of civilian control of the State? We argue that civilian dominance of politics is achieved once civilianized institutions are adopted and sufficient time has passed to permit: (1) the development of a shared norm of civilian control within the military and (2) learning among military elites that fosters a belief that civilian rule is robust to military challenges. As a result, civilian control is self-reinforcing. We evaluate these claims by developing and validating a latent variable model of self-reinforcing institutional dynamics. We generate estimates of civilian control for all countries, 1945–2010, and find strong evidence that civilian control self-reinforces, but incrementally and over the course of several decades.

AbstractTerritorial contenders are political entities that control populated territories but lack recognition as sovereigns. They pose existential threats to their host states by reshaping recognized borders and generating zones of contested authority. States have strong incentives to eliminate them, and yet they persist—developing countries host an average of three territorial contenders within their borders. Understanding why territorial contenders survive and how they die is a critical puzzle in the study of state making. International forces offer important, if overlooked, explanations for these seemingly domestic processes. First, we argue that international rivals perpetuate the existence of territorial contenders by undermining a state's ability to reintegrate them through peaceful negotiations or by force. Secondly, the international human rights treaty regime provides a mechanism by which territorial contenders can galvanize support from potential allies, increasing a state's willingness and ability to resolve these disputes through peaceful reintegration processes.

AbstractBorder politics are a salient component of high international politics. States are increasingly building infrastructure to ''secure'' their borders. We introduce the concept of border orientation to describe the extent to which the state is committed to the spatial display of capacities to control the terms of penetration of its national borders. Border orientation provides a lens through which to analyze resistance to globalization, growing populism, and the consequences of intensified border politics. We measure border orientation using novel, geospatial data on the built environment along the world's borders and theorize that real and perceived pressures of globalization have resulted in more controlling forms of border governance. Empirical evidence supports this claim: States build more along their borders when faced with economic, cultural, and security‐based anxieties. Border orientation enhances the study of border politics, complementing the politics of territorial division with a richer politics of liminal securitization and its consequences.

Democratic leaders are commonly thought to be more likely than autocrats to select into conflicts where the ex ante probability of victory is high. We construct a novel empirical test of this notion by comparing democracies to various types of autocracies and determining which states are most likely to initiate disputes against relatively strong or weak opponents. Contrary to common belief, we find that democracies are not more selective than most forms of autocracy. Only military regimes demonstrate unique patterns of target selection, with these states being particularly likely to initiate disputes against relatively strong opponents. Our findings suggest a need to further scrutinize the conventional wisdom on democratic target selection and to disaggregate autocratic regimes into more refined categories when doing so.

The Border Crossings of the World (BCW) dataset explores state authority spatially by collecting information about infrastructure built where highways cross internationally recognized borders. This geolocated information is recorded using high-altitude imagery from 1993 to 2020. We describe how the data were collected, demonstrate the dataset's utility, and offer advice and best practices regarding use of the data. These data present clear evidence of visible and long-term state investments in authoritative displays of states' intention to 'filter' entry into and exit out of their national jurisdiction. Researchers can use these data to test theories on the causes and consequences of border hardening for security outcomes, border management cooperation, political violence, terrorism, trade and migration flows, transnational crime patterns, and human rights conditions. Because the data are precisely geolocated, they are easy to combine with existing spatial datasets.

Counting repressive events is difficult because state leaders have an incentive to conceal actions of their subordinates and destroy evidence of abuse. In this article, we extend existing latent variable modeling techniques in the study of repression to account for the uncertainty inherent in count data generated for this type of difficult-to-observe event. We demonstrate the utility of the model by focusing on a dataset that defines 'one-sided-killing' as government-caused deaths of non-combatants. In addition to generating more precise estimates of latent repression levels, the model also estimates the probability that a state engaged in one-sided-killing and the predictive distribution of deaths for each country-year in the dataset. These new event-based, count estimates will be useful for researchers interested in this type of data but skeptical of the comparability of such events across countries and over time. Our modeling framework also provides a principled method for inferring unobserved count variables based on conceptually related categorical information.

Researchers face a tradeoff when applying latent variable models to time-series, cross-sectional data. Static models minimize bias but assume data are temporally independent, resulting in a loss of efficiency. Dynamic models explicitly model temporal data structures, but smooth estimates of the latent trait across time, resulting in bias when the latent trait changes rapidly. We address this tradeoff by investigating a new approach for modeling and evaluating latent variable estimates: a robust dynamic model. The robust model is capable of minimizing bias and accommodating volatile changes in the latent trait. Simulations demonstrate that the robust model outperforms other models when the underlying latent trait is subject to rapid change, and is equivalent to the dynamic model in the absence of volatility. We reproduce latent estimates from studies of judicial ideology and democracy. For judicial ideology, the robust model uncovers shocks in judicial voting patterns that were not previously identified in the dynamic model. For democracy, the robust model provides more precise estimates of sudden institutional changes such as the imposition of martial law in the Philippines (1972–1981) and the short-lived Saur Revolution in Afghanistan (1978). Overall, the robust model is a useful alternative to the standard dynamic model for modeling latent traits that change rapidly over time.

Abstract
In a recent article, Gibler, Miller, and Little (2016) (GML) conduct an extensive review of the Militarized Interstate Dispute (MID) data between the years 1816 and 2001, highlighting possible inaccuracies and recommending a substantial number of changes to the data. They contend that, in several instances, analyses with their revised data lead to substantively different inferences. Here, we review GML's MID drop and merge recommendations and reevaluate the substantive impact of their changes. We are in agreement with about 76 percent of the recommended drops and merges. However, we find that some of the purported overturned findings in GML's replications are not due to their data, but rather to the strategies they employ for replication. We reexamine these findings and conclude that the remaining differences in inference stemming from the variations in the MID data are rare and modest in scope.