Daniel W. Hill

An Empirical Evaluation of Explanations for State Repression

The empirical literature that examines cross-national patterns of state repression seeks to discover a set of political, economic, and social conditions that are consistently associated with government violations of human rights. Null hypothesis significance testing is the most common way of examining the relationship between repression and concepts of interest, but we argue that it is inadequate for this goal, and has produced potentially misleading results. To remedy this deficiency in the literature we use cross-validation and random forests to determine the predictive power of measures of concepts the literature identifies as important causes of repression. We find that few of these measures are able to substantially improve the predictive power of statistical models of repression. Further, the most studied concept in the literature, democratic political institutions, predicts certain kinds of repression much more accurately than others. We argue that this is due to conceptual and operational overlap between democracy and certain kinds of state repression. Finally, we argue that the impressive performance of certain features of domestic legal systems, as well as some economic and demographic factors, justifies a stronger focus on these concepts in future studies of repression.

Modeling Two Types of Peace: The Zero-inflated Ordered Probit (ZiOP) Model in Conflict Research

A growing body of applied research on political violence employs split-population models to address problems of zero inflation in conflict event counts and related binary dependent variables. Nevertheless, conflict researchers typically use standard ordered probit models to study discrete ordered dependent variables characterized by excessive zeros (e.g., levels of conflict). This study familiarizes conflict scholars with a recently proposed split-population model—the zero-inflated ordered probit (ZiOP) model—that explicitly addresses the econometric challenges that researchers face when using a “zero-inflated” ordered dependent variable. We show that the ZiOP model provides more than an econometric fix: it provides substantively rich information about the heterogeneous pool of “peace” observations that exist in zero-inflated ordinal variables that measure violent conflict. We demonstrate the usefulness of the model through Monte Carlo experiments and replications of published work and also show that the substantive effects of covariates derived from the ZiOP model can reveal nonmonotonic relationships between these covariates and one’s conflict probabilities of interest.

Avoiding Obligation Reservations to Human Rights Treaties

This article examines the decisions of governments to enter reservations upon ratification of international human rights treaties. I argue that, in the context of the human rights regime, reservations are simply attempts to avoid international legal obligations where they would be consequential. I develop an explanation for their use that focuses on the following two factors: the legal constraints that already exist in domestic law and the likelihood that international agreements will be enforced by domestic courts. Using an original measure of domestic legal protection of civil, political, and personal integrity rights, I find evidence that governments are more likely to enter reservations when domestic legal standards are lax compared to those in the treaty and when judiciaries are likely to enforce treaty-based obligations. This suggests that full adoption of international human rights treaties is more likely when treaties will not create genuine domestic legal constraints and that explanations for treaty adoption and implementation must take reservations into account. It also suggests that adoption of international human rights law is best explained by the specific legal institutions that relate to domestic enforcement rather than broad distinctions between democratic/autocratic political institutions.

Torture and the limits of democratic institutions

What are the limits of democracy’s positive influence on human rights? In this article, we argue that contested elections and powerful courts provide leaders with different incentives with regard to hiding torture. Because government torture is generally targeted at individuals that voters find threatening, institutions that reflect public opinion – like electoral contestation – are associated with higher levels of government abuse that leave scars on the victim’s body. Other institutions – like powerful courts – protect the rights of political minorities. Leaders in countries with powerful courts prefer plausible deniability of rights violations and consequently employ higher levels of clean torture, which leaves no scars. We test our hypotheses using data from the Ill-Treatment and Torture (ITT) Data Collection Project that distinguish between Amnesty International (AI) allegations of scarring and clean torture. We employ an undercount negative binomial that accounts for AI’s (in)ability to obtain information about torture. The model assumes that some incidents of torture go unreported and allows the extent of underreporting to vary across countries/years. Estimates from the model yield considerable statistical and substantive support for our hypotheses.

How much terror? Dissidents, governments, institutions, and the cross-national study of terror attacks

Our knowledge of the set of concepts that influence the number of terror attacks experienced by different countries is rudimentary. Existing work on the incidence of terror focuses upon the structural characteristics of polities, economies, and societies, and fails to place competition between dissidents and states center stage. It also tends to treat terror as isolated from other tactics that dissident groups might use to pressure the state. This study addresses these shortcomings by placing government and dissident group behavior at the center of the analysis. Drawing on arguments from the larger literature on dissent and repression, we argue that government behavior and dissident behavior are likely to be more important determinants of terror attacks than structural factors. We scour the literature for existing arguments to round out our model specification, and evaluate hypotheses using Bayesian statistical techniques and a broad scope of relevant data. For many of our independent variables we construct indices using measurement models that are able to account for measurement error and missing data, resulting in a more comprehensive set of data than previous studies. The results demonstrate that measures of government and dissident behavior have more explanatory power than measures of the concepts that populate existing research.

Modeling Terror Attacks: A Cross-National, Out-of-Sample Study

We have developed a Bayesian, multi-level statistical model that contains at its center a theoretical account of dissidents’ choice to adopt terror tactics. The model has been estimated using data from all countries over the world during the 1970s, 1980s, and 1990s, but the out-of-sample performance of the model warrants investigation. Policy makers have considerable interest in being able to forecast terror attacks, even at an aggregated level of granularity such as the country-year. Scholars have yet to supply many of these models, and we provide our effort as a useful baseline that can be used to evaluate the performance of more region and country specific models to be developed in the future. Having scoured the literature to identify relevant covariates to use as controls in our dissident tactic centered model, our multi-decade, cross-national estimates make an especially attractive candidate for establishing a general baseline. Our analysis evaluates the sensitivity and specificity of the model’s performance, as well as the conditional distributions of positive and negative predicted values. Both the number of false positives and false negatives produced by the model suggest that it is not ready for use in policy planning. It’s value, then, is as a baseline against which to evaluate the performance of future forecast models.

Democracy and police violence

Are police agencies less likely to use torture in democracies than in non-democracies? Much empirical research has shown that democracies are less likely to engage in torture in general, but most of this research does not distinguish among victim types or state agencies. Using the Ill-Treatment and Torture (ITT) Data, we focus on police agencies and evaluate whether they are less likely to use torture against (separately) political dissidents, criminals, and marginalized communities. Using logistic regressions with random effects, we find that the well-established and relatively high level of democracies’ respect for the rights of dissidents extends to police agencies as well. However, we find weaker statistical evidence that police agencies in democracies are less likely to use torture against criminals, and no evidence that they are less likely to torture marginalized communities. Our results suggest that one of the most robust empirical facts in the literature must be qualified. The protection from violence offered by democratic institutions does not seem to generalize beyond violence directly related to political competition and dissent.