Suchergebnisse

Does military intervention affect civilian death tolls? Existing research has focused on international actors' ability to limit ongoing slaughter but has not examined their ability to prevent the emergence or escalation of such killing. I develop a theory of government killing that accounts not only for the government's decision to kill civilians but also for the transference of the killing order from leader to perpetrator, and for the perpetrator's implementation of that order. Focusing on the principal–agent relationship produces new expectations about the effects of military intervention on government killing. I find that international actors are well equipped to limit civilian slaughter: intervention supporting the government decreases the likelihood that a government orders civilians killed. Intervention against the government leads to a decrease in death tolls when killing occurs. Ultimately, supportive intervention is a useful means of preventing government killing, while oppositional intervention limits its escalation once it begins.

A state-dependent dynamic system is one in which (1) the marginal effect ofxonyat timet() depends on the prior value of the dependent variable, and (2) the persistence of the dependent variable () depends onxt. We present a methodological strategy for dealing with state-dependent dynamic systems and demonstrate the consequences of ignoring state-dependence. As an applied example, we find evidence of state-dependence in the relationship between presidential approval and economic performance: high unemployment rates are most damaging to presidential approval among presidents with the highest initial approval ratings.

Political scientists presenting binary dependent variable (BDV) models often hypothesize that variables interact to influence the probability of an event, Pr(Y). The current typical approach to testing such hypotheses is (1) estimate a logit or probit model with a product term, (2) test the hypothesis by determining whether the coefficient for this term is statistically significant, and (3) characterize the nature of any interaction detected by describing how the estimated effect of one variable on Pr(Y) varies with the value of another. This approach makes a statistically significant product term necessary to support the interaction hypothesis. We show that a statistically significant product term is neither necessary nor sufficient for variables to interact meaningfully in influencing Pr(Y). Indeed, even when a logit or probit model contains no product term, the effect of one variable on Pr(Y) may be strongly related to the value of another. We present a strategy for testing for interaction in a BDV model, including guidance on when to include a product term. Adapted from the source document.

A wealth of literature argues that domestic institutions can sometimes restrain government repression. In this article, we highlight an institution tasked specifically with protecting and promoting human rights: the National Human Rights Institution (NHRI). Although common international standards exist, NHRIs exhibit substantial variation in their organization, the rights that they protect, the activities they permit, and the manner in which they appoint their members. Scholarship to date has conceptualized and measured NHRIs dichotomously; an NHRI either exists or it does not. We present data that highlights NHRI heterogeneity collected via content analysis of NHRI annual reports, NHRI websites, national constitutions, government legislation, and other sources. Using these data, we show NHRIs that can publish their findings and NHRIs that can punish offenders are each associated with less state torture. These data will allow future researchers to better explore important questions regarding NHRI origins, design, processes, and effectiveness.