Suchergebnisse

To document human rights, monitoring organizations establish a standard of accountability, or a baseline set of expectations that states ought to meet in order to be considered respectful of human rights. If the standard of accountability has meaningfully changed, then the categorized variables from human rights documents will mask real improvements. Cingranelli and Filippov question whether the standard of accountability is changing and whether data on mass killings are part of the same underlying conceptual process of repression as other abuses. These claims are used to justify alternative models, showing no improvement in human rights. However, by focusing on the coding process, the authors misunderstand that the standard of accountability is about how monitoring organizations produce documents in the first place and not how academics use published documents to create data. Simulations and latent variables that model time in a substantively meaningful way validate the conclusion that human rights are improving.

The observation, measurement, and analysis of violent and contentious processes are essential parts of the scientific study of peace and conflict. However, concepts such as the level of repression, the number of individuals killed during a civil war, or the perception of members of an out-group, are often by definition difficult to observe directly. This is because governments, non-state groups, NGOs, international organizations, monitoring organizations, and other actors are not incentivized to make information about their actions systematically observable to analysts. In this context, latent variable models can play a valuable role by aggregating various behavioral indicators and signals together to help measure latent concepts of interest that would not otherwise be directly observable. Each of the articles in this special issue uses some form of a latent variable model or related measurement model to bring together observable pieces of information and estimate a set of values for the underlying theoretical concept of interest. Each of the articles pays special attention to the processes that make the observation of peace and conflict processes so challenging. As we highlight throughout this introductory article, the unifying framework we present in this special issue is validation. Though the substantive content of each of the articles in this special issue varies, they represent the diversity of substantive interests that span the study of peace and conflict, broadly conceived. Overall, we hope that the special issue becomes a standard reference for scholars interested in developing and validating new measurement models for the study of peace and conflict.

AbstractScholars systematically mismeasure power resources and military burdens by using gross domestic product (GDP) as a proxy for the income states can devote to arming. The core problem is that GDP confounds two conceptually distinct forms of income into one additive indicator. Subsistence income represents resources needed to provide the "bread" necessary to cover the basic subsistence needs of the population. Surplus income represents the remaining resources that could be allocated to "guns" or "butter." Our new measure of surplus domestic product (SDP) corrects for this measurement error by decomposing subsistence income and surplus income from total GDP. Validation exercises demonstrate that SDP outperforms GDP at measuring the distribution of power resources. Though theoretically we expect states' decisions to arm are influenced by the distribution of power; empirical models using GDP find mixed support for this expectation. Strikingly, using SDP reveals strong support for this proposition.

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.

AbstractUntil recently, researchers who wanted to examine the determinants of state respect for most specific negative rights (i.e., physical integrity and empowerment rights) needed to rely on data from the CIRI or the Political Terror Scale (PTS). The new Varieties of Democracy (V-Dem) dataset offers scholars a potential alternative to the individual human rights variables from CIRI. We analyze a set of key Cingranelli–Richards (CIRI) Human Rights Data Project and V-Dem negative rights indicators, finding unusual and unexpectedly large patterns of disagreement between the two sets. First, we discuss the new V-Dem dataset by comparing it to the disaggregated CIRI indicators, discussing the history of each project, and describing its empirical domain. Second, we identify a set of disaggregated human rights measures that are similar across the two datasets and discuss each project's measurement approach. Third, we examine how these measures compare to each other empirically, showing that they diverge considerably across both time and space. These findings point to several important directions for future work, such as how conceptual approaches and measurement strategies affect rights scores. For the time being, our findings suggest that researchers should think carefully about using the measures as substitutes.

How does a state's source of wealth condition the domain in which it seeks to project influence? We argue that what a state makes conditions what they take. Specifically, the less states rely on land rents to acquire wealth, the less interested they will be in seeking control over territory and the more interested they will be in securing access to distant markets. We develop and test several observable implications that should follow whether this proposition is true. First, as states become less economically dependent on territory, they should be less likely to fight over territory; second, those states should be more likely to both invest in power projection capabilities and subsequently project power at greater distances. Our findings support our theory. These results are robust across a variety of model specifications that take into account potential confounds, such as regime type, economic development, threat, and geography.

How do international norms affect respect for human rights? We report the results of an audit experiment with foreign missions that investigates the extent to which state agents observe international norms and react to the potential of international shaming. Our experiment involved emailing 669 foreign diplomatic missions in the United States, Canada, and the United Kingdom with requests to contact domestic prisoners. According to the United Nations, prisoners have the right for individuals to contact them. We randomly varied (1) whether we reminded embassies about the existence of an international norm permitting prisoner contact and (2) whether the putative email sender is associated with a fictitious human rights organization and, thereby, has the capacity to shame missions through naming and shaming for violating this norm. We find strong evidence for the positive effect of international norms on state respect for human rights. Contra to our expectations, though, we find that the potential of international shaming does not increase the probability of state compliance. The positive effect of the norms cue disappears when it is coupled with the shaming cue, suggesting that shaming might have a 'backfire' effect.

How do international norms affect respect for human rights? We report the results of an audit experiment with foreign missions that investigates the extent to which state agents observe international norms and react to the potential of international shaming. Our experiment involved emailing 669 foreign diplomatic missions in the United States, Canada, and the United Kingdom with requests to contact domestic prisoners. According to the United Nations, prisoners have the right for individuals to contact them. We randomly varied (1) whether we reminded embassies about the existence of an international norm permitting prisoner contact and (2) whether the putative email sender is associated with a fictitious human rights organization and, thereby, has the capacity to shame missions through naming and shaming for violating this norm. We find strong evidence for the positive effect of international norms on state respect for human rights. Contra to our expectations, though, we find that the potential of international shaming does not increase the probability of state compliance. The positive effect of the norms cue disappears when it is coupled with the shaming cue, suggesting that shaming might have a 'backfire' effect.

Scholarship suggests the profits from conquest have decreased over time. Given this, why were some states faster to abandon profit-motivated conquest, and why are some still seeking wealth from territorial control? We argue that land-rent dependence influences a regime's economic preference for territory. The more a state depends on rents extracted from land (i.e., the more land-oriented the economy), the greater its willingness to invest in securing control of territory. We develop a novel measure of land orientation, with 200 years of data, to evaluate the linkages between land orientation and military competition over territory. Across 160 regression models, we find robust evidence that land orientation predicts territorial competition. These results hold in both democracies and autocracies. The global reduction in land-oriented states offers a plausible explanation for the decline in the number of large-scale territorial conquests. Our findings also explain why some states retain strong economic motivations for conquest.