Research and Code — Michael P. Colaresi

Below are links to books, articles/proceedings, +data/code from projects I have been involved in. If you have any questions, please contact me at mcolaresi@pitt.edu. My CV can be found here.

Books

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Democracy Declassified: The Secrecy Dilemma In National Security | Michael Colaresi | 2014 | Oxford University Press

Democracy Declassified takes an in-depth look at one of the most enduring and debated policy questions: how to balance secrecy with accountability. It explores instances of secrecy dilemmas through history and across the globe, including WikiLeaks and Edward Snowden and the NSA scandal, and catalogs national security institutions in democracies from the 1970s through 2006, showing evidence that oversight institutions have been expanding across time and space. Evidence is presented that countries that build and maintain oversight institutions are better able to manage foreign policy that promotes national interests.

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Strategic Rivalries in World Politics: Position, Space and Conflict Escalation | Michael Colaresi, Karen Rasler and William R. Thompson | 2007 | Cambridge University Press

International conflict is neither random nor inexplicable. It is highly structured by antagonisms between a relatively small set of states that regard each other as rivals. Examining the 173 strategic rivalries in operation throughout the nineteenth and twentieth centuries, Strategic Rivalries in World Politics identifies the differences rivalries make in the probability of conflict escalation and analyzes how they interact with serial crises, arms races, alliances and capability advantages. The authors distinguish between rivalries concerning territorial disagreement (space) and rivalries concerning status and influence (position) and show how each leads to markedly different patterns of conflict escalation. They argue that rivals are more likely to engage in international conflict with their antagonists than non-rival pairs of states and conclude with an assessment of whether we can expect democratic peace, economic development and economic interdependence to constrain rivalry-induced conflict.

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Scare Tactics: The Politics of International Rivalry | Michael Colaresi | 2005 | Syracuse University Press

Why do international situations spiral out of control and into war? Why do conflicts finally wind down after years, if not decades, of tension? Various faults in conventional thinking, ranging from relying on indeterminate predictions to ignoring the interaction between domestic and international events, have impeded adequate explanations for the continuation, escalation, and dampening of rivalry conflict. Scare Tactics: The Politics of International Rivalry explains how domestic institutions and interactions among nations converge to create incentives for either war or peace. Specifically, domestic pressure to continue a rivalry and resist capitulating to the "enemy" can be exacerbated in situations where elites benefit from fear-mongering, a process referred to as "rivalry outbidding." When rivalry outbidding becomes fused with pressure to change the status quo, even a risky escalation may be preferable to cooperation or rivalry maintenance. The eventual outcomes of such dynamic two-level pressures, if unchecked, are increased conflict, destruction, and death. However, if leaders can resist pressures to escalate threats and step up rivalries, a deteriorating status quo can instead spur cooperation and peace.

Journals and Proceedings

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Human Rights, Violence, Analytics, Data Visualization

HR-VEAW: A Human Rights Violation Exploration, Analytics, and Warning System | Zhang, et al | 2022 | Proceedings of the EDBT/ICDT

Human Rights, Violence, Analytics, Data Visualization

The availability of information from social media, such as tweets, and human rights monitors, such as Amnesty International, Human Rights Watch, and the US State Department has led to new opportunities to measure repression and human rights protections in higher resolution. In this paper, we present HR-VEAW, a Human Rights Violation Exploration, Analytics, and Warning system, to support understanding of social conflict dynamics and human rights violations/protections with quantitative data. After briefly discussing HR-VEAW’s data acquisition and analysis components, we demonstrate how it visualizes rich spatio-temporal and conceptual information, enabling the examination of changes in patterns of violation and protection in aggregate over time, or across both space and time. This way HR-VEAW helps to explain social instability and conflicts and to guide decision-making, theorizing, and predictions.

Human Rights, Violence, Analytics, Data Visualization

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United they stand: Findings from an escalation prediction competition | Vesco, et al | 2022 | International Interactions

This article presents results and lessons learned from a prediction competition organized by ViEWS to improve collective scientific knowledge on forecasting (de-)escalation in Africa. The competition call asked participants to forecast changes in state-based violence for the true future (October 2020–March 2021) as well as for a held-out test partition. An external scoring committee, independent from both the organizers and participants, was formed to evaluate the models based on both qualitative and quantitative criteria, including performance, novelty, uniqueness, and replicability. All models contributed to advance the research frontier by providing novel methodological or theoretical insight, including new data, or adopting innovative model specifications. While we discuss several facets of the competition that could be improved moving forward, the collection passes an important test. When we build a simple ensemble prediction model—which draws on the unique insights of each contribution to differing degrees—we can measure an improvement in the prediction from the group, over and above what the average individual model can achieve. This wisdom of the crowd effect suggests that future competitions that build on both the successes and failures of ours, can contribute to scientific knowledge by incentivizing diverse contributions as well as focusing a group’s attention on a common problem.

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Lessons from an escalation prediction competition | Hegre, Vesco, and Colaresi | 2022 | International Interactions

Recent research on the forecasting of violence has mostly focused on predicting the presence or absence of conflict in a given location, while much less attention has been paid to predicting changes in violence. We organized a prediction competition to forecast changes in state-based violence both for the true future and for a test partition. We received contributions from 15 international teams. The models leverage new insight on the targeted problem, insisting on methodological advances, new data and features, and innovative frameworks which contribute to the research frontiers from various perspectives. This article introduces the competition, presents the main innovations fostered by the teams and discusses ways to further expand and improve upon this wisdom of the crowd. We show that an optimal modeling approach builds on a good number of the presented contributions and new evaluation metrics are needed to capture substantial models’ improvements and reward unique insights.

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Political violence, Machine Learning, Ensembles, Prediction

Revising and Evaluating the ViEWS Political Violence Early Warning System | Hegre, et al | 2020 | Journal of Peace Research

Political violence, Machine Learning, Ensembles, Prediction

This article presents an update to the ViEWS political Violence Early-Warning System. This update introduces (1) a new infrastructure for training, evaluating, and weighting models that allows us to more optimally combine constituent models into ensembles, and (2) a number of new forecasting models that contribute to improve overall performance, in particular with respect to effectively classifying high- and low-risk cases. Our improved evaluation procedures allow us to develop models that specialize in either the immediate or the more distant future. We also present a formal, ‘retrospective’ evaluation of how well ViEWS has done since we started publishing our forecasts from July 2018 up to December 2019. Our metrics show that ViEWS is performing well when compared to previous out-of-sample forecasts for the 2015–17 period. Finally, we present our new forecasts for the January 2020–December 2022 period. We continue to predict a near-constant situation of conflict in Nigeria, Somalia, and DRC, but see some signs of decreased risk in Cameroon and Mozambique.

Political violence, Machine Learning, Ensembles, Prediction

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human rights, computational social science, information-communication technology, measurement, PULSAR

Human Rights are (Increasingly) Plural | Baekkwan Park. Kevin Greene, and Michael Colaresi | 2020 | American Political Science Review

human rights, computational social science, information-communication technology, measurement, PULSAR

This manuscript helps to resolve the ongoing debate concerning the effect of information communication technology on human rights monitoring. We re-conceptualize human rights as a taxonomy of nested rights that are judged in textual reports and argue that the increasing density of available information should manifest in deeper taxonomies of human rights. With a new automated system, using supervised learning algorithms, we are able to extract the implicit taxonomies of rights that were judged in texts by the US State Department, Amnesty International, and Human Rights Watch over time. Our analysis provides new, clear evidence of change in the structure of these taxonomies as well as in the attention to specific rights and the sharpness of distinctions between rights. Our findings bridge the natural language processing and human rights communities and allow a deeper understanding of how changes in technology have affected the recording of human rights over time.

human rights, computational social science, information-communication technology, measurement, PULSAR

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disinformation, democracy, surveillance, computational social science, social media

How our misunderstanding of the digital and computing revolutions puts democracy at risk (and what to do about it) | Michael Colaresi | 2020 | Critical Quarterly

disinformation, democracy, surveillance, computational social science, social media

Abstract

Today, the digital and computing revolutions we are living through give the false impression that risk is evaporating across the GPUs of computing clusters, deftly driven around by self‐driving cars, or is being arbitraged against at near light‐speed by financial algorithms. Those researchers that extol the virtues of the computing and digital revolutions emphasize the access to information and connections empowered by the internet, smart phones, and social media. Yet, these aggregate sketches obscure the fact that unequal access to information allows some, but not all, to manage these risks. Elites can block and warp access to the internet and individual information environments for their own ends. Social media amplifies anxiety and addiction, especially for vulnerable populations. Moreover, there is recent evidence that even news alerts on phones, by optimizing attention‐grabbing text instead of knowledge, polarize instead of generating common knowledge. In this essay, I hope to lay out a clear logic for why unequal access to technology that reduces specific predictive risks for some (using big data and machine learning) increases anxiety and perceptual risks for most others, including democratic citizens in the US and Europe.

disinformation, democracy, surveillance, computational social science, social media

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human rights, PULSAR, machine learning, computational social science

How to Teach Machines to Read Human Rights Reports and Identify Judgments at Scale: Introducing PULSAR | Baekkwan Park, Kevin Greene, Michael Colaresi | 2020 | Journal of Human Rights

human rights, PULSAR, machine learning, computational social science

Abstract

The accelerating availability of information from human rights monitors such as Amnesty International, Human Rights Watch, and the US State Department has led to new opportunities to measure repression and human rights protections in higher resolution. However, to date, most approaches that attempt to automatically structure textual reports use simple, lower-dimensional observations such as the counts of words that ignore syntax and word order. While these representations are useful for some applications, they limit the inferences scholars and policy-makers can extract from human rights reports. In this article, we present a new system, PULSAR, that takes syntax and word order into account. This system uniquely allows researchers to extract both the judgements and the aspects/rights being judged from texts at scale. We illustrate that this more detailed information is useful both for improving predictions of physical integrity rights and women's political rights, but also for generating machine learning models that are more interpretable than conventional specifications. This latter benefit holds the promise of coherently connecting qualitative and quantitative analyses of human rights texts.

human rights, PULSAR, machine learning, computational social science

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human rights, machine learning, computational social science, PULSAR

Beyond a Bag of Words | Baekkwan Park, Michael Colaresi, Kevin Greene | 2019 | Peace Economics, Peace Science and Public Policy

human rights, machine learning, computational social science, PULSAR

Abstract

Sentiment, judgments and expressed positions are crucial concepts across international relations and the social sciences more generally. Yet, contemporary quantitative research has conventionally avoided the most direct and nuanced source of this information: political and social texts. In contrast, qualitative research has long relied on the patterns in texts to understand detailed trends in public opinion, social issues, the terms of in- ternational alliances, and the positions of politicians. Yet, qualitative human reading does not scale to the ac- celerating mass of digital information available currently. Researchers are in need of automated tools that can extract meaningful opinions and judgments from texts. Thus, there is an emerging opportunity to marry the model-based, inferential focus of quantitative methodology, as exemplified by ideal point models, with high resolution, qualitative interpretations of language and positions. We suggest that using alternatives to simple bag of words (BOW) representations and re-focusing on aspect-sentiment representations of text will aid re- searchers in systematically extracting people’s judgments and what is being judged at scale. The experimental results below show that our approach which automates the extraction of aspect and sentiment MWE pairs, out- performs BOW in classification tasks, while providing more interpretable parameters. By connecting expressed sentiment and the aspects being judged, PULSAR (Parsing Unstructured Language into Sentiment-Aspect Rep- resentations) also has deep implications for understanding the underlying dimensionality of issue positions and ideal points estimated with text. Our approach to parsing text into aspects-sentiment expressions recovers both expressive phrases (akin to categorical votes), as well as the aspects that are being judged (akin to bills). Thus, PULSAR or future systems like it, open up new avenues for the systematic analysis of high-dimensional opinions and judgments at scale within existing ideal point models.

human rights, machine learning, computational social science, PULSAR

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ViEWS: A political violence early-warning system | Hegre, et al, | 2019 | Journal of Peace Research

Abstract

This article presents ViEWS – a political violence early-warning system that seeks to be maximally transparent, publicly available, and have uniform coverage, and sketches the methodological innovations required to achieve these objectives. ViEWS produces monthly forecasts at the country and subnational level for 36 months into the future and all three UCDP types of organized violence: state-based conflict, non-state conflict, and one-sided violence in Africa. The article presents the methodology and data behind these forecasts, evaluates their predictive performance, provides selected forecasts for October 2018 through October 2021, and indicates future extensions. ViEWS is built as an ensemble of constituent models designed to optimize its predictions. Each of these represents a theme that the conflict research literature suggests is relevant, or implements a specific statistical/machine-learning approach. Current forecasts indicate a persistence of conflict in regions in Africa with a recent history of political violence but also alert to new conflicts such as in Southern Cameroon and Northern Mozambique. The subsequent evaluation additionally shows that ViEWS is able to accurately capture the long-term behavior of established political violence, as well as diffusion processes such as the spread of violence in Cameroon. The performance demonstrated here indicates that ViEWS can be a useful complement to non-public conflict-warning systems, and also serves as a reference against which future improvements can be evaluated.

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Machine Learning Human Rights and Wrongs | Kevin Greene, Baekkwan Park and Michael Colaresi | 2018 Political Analysis

Abstract

There is an ongoing debate about whether human rights standards have changed over the last 30 years. The evidence for or against this shift relies upon indicators created by human coders reading the texts of human rights reports. To help resolve this debate, we suggest translating the question of changing standards into a supervised learning problem. From this perspective, the application of consistent standards over time implies a time-constant mapping from the textual features in reports to the human coded scores. Alternatively, if the meaning of abuses have evolved over time, then the same textual features will be labeled with different numerical scores at distinct times. Of course, while the mapping from natural language to numerical human rights score is a highly complicated function, we show that these two distinct data generation processes imply divergent overall patterns of accuracy when we train a wide variety of algorithms on older versus newer sets of observations to learn how to automatically label texts with scores. Our results are consistent with the expectation that standards of human rights have changed over time.

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civil war, forecasting, machine learning, methodology, visualization, conflict

Do the Robot: Lessons from Machine Learning to Improve Conflict Forecasting | Michael Colaresi and Zuhaib Mahmood | Journal of Peace Research | 2017

civil war, forecasting, machine learning, methodology, visualization, conflict

Abstract:

Increasingly, scholars interested in understanding conflict processes have turned to evaluating out-of-sample forecasts to judge and compare the usefulness of their models. Research in this vein has made significant progress in identifying and avoiding the problem of overfitting sample data. Yet there has been less research providing strategies and tools to practically improve the out-of-sample performance of existing models and connect forecasting improvement to the goal of theory development in conflict studies. In this article, we fill this void by building on lessons from machine learning research. We highlight a set of iterative tasks, which David Blei terms ‘Box’s loop’, that can be summarized as build, compute, critique, and think. While the initial steps of Box’s loop will be familiar to researchers, the underutilized process of model criticism allows researchers to iteratively learn more useful representations of the data generation process from the discrepancies between the trained model and held-out data. To benefit from iterative model criticism, we advise researchers not only to split their available data into separate training and test sets, but also sample from their training data to allow for iterative model development, as is common in machine learning applications. Since practical tools for model criticism in particular are underdeveloped, we also provide software for new visualizations that build upon already existing tools. We use models of civil war onset to provide an illustration of how our machine learning-inspired research design can simultaneously improve out-of-sample forecasting perfor- mance and identify useful theoretical contributions. We believe these research strategies can complement existing designs to accelerate innovations across conflict processes.

civil war, forecasting, machine learning, methodology, visualization, conflict

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rivalry, civil war, endogeneity, international, conflict, international relations theory

Fighting Abroad, Fighting at Home (and Vice Versa): Identifying the Relationship Between Civil and Interstate War with Fewer Assumptions | Michael Colaresi | Oxford Encyclopedia of Politics | 2017

rivalry, civil war, endogeneity, international, conflict, international relations theory

Abstract:

There has been increasing scholarly attention paid to the relationship between civil war and international disputes. While this literature includes a rich set of theoretical expectation, the empirical evidence offered to support them thus far has included several important shortcoming. Most crucially, previous influential models of the effect of civil war on interstate disputes assume that civil war initiation and duration is exogenous from underlying international hostilities. Here, I show that this assumption neither matches the theoretical mechanisms being analyzed, nor is it necessary to bring quantitative evidence to bear on interstices of domestic and interstate conflict. I use special regressor methods, suggested by Lewbel (2000) to account for the cross-level, monadic-to-dyadic, relationship, as well as the potential for endogeneity. I illustrate why conventional single-equation approaches, as well as parametric bivariate probit models produce biased inferences on the effect of civil war on interstate disputes. Using the negative of the log of inter-capital distance as the special regressor, I show that there is an absence of clear evidence for an exogenous effect of civil war on interstate conflict. Instead, more research should explore the role of dynamic international hostility in causing both conflict processes.

rivalry, civil war, endogeneity, international, conflict, international relations theory

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replication, game theory, international relations theory, publication, methodology

Preplication, Replication: A Proposal to Efficiently Upgrade Journal Replication Standards | Michael Colaresi | International Studies Perspectives | 2016

replication, game theory, international relations theory, publication, methodology

Abstract:

Despite 20 years of progress in promoting replication standards in International Relations (IR), significant problems remain in both the provision of data and the incentives to replicate published research. While replicable research is a public good, there appear to be private incentives for researchers to follow socially suboptimal research strategies. The current situation has led to a growing concern in IR, as well as across the social sciences, that published research findings may not represent accurate appraisals of the evidence on particular research questions. In this article, I discuss the role of private information in the publication process and review the incentives for producing replicable and nonreplicable research. A small, but potentially important, change in a journal’s workflow could both deter the publication of nonreplicable work and lower the costs for researchers to build and expand upon existing published research. The suggestion, termed Preplication, is for journals to run the replication data and code for conditionally accepted articles before publication, just as journals routinely check for compliance with style guides. This change could be implemented alongside other revisions to journal policies around the discipline. In fact, Preplication is already in use at several journals, and I provide an update as to how the process has worked at International Interactions.

replication, game theory, international relations theory, publication, methodology

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public-private sector cooperation, conflict, accountability, civil war, militias, domestic

Risk Mitigation, Regime Security, and Militias: Beyond Coup-proofing | Sabine Carey, Michael Colaresi and Neil Mitchell | International Studies Quarterly | 2016

public-private sector cooperation, conflict, accountability, civil war, militias, domestic

Abstract:

In Thailand, India, Libya, and elsewhere, governments arm the populace or call up volunteers in irregular armed groups despite the risks this entails. The widespread presence of these militias, outside the context of state failure, challenges the expectation that governments uniformly consolidate the tools of violence. Drawing on the logic of delegation, we resolve this puzzle by arguing that governments have multiple incentives to form armed groups with a recognized link to the state but outside of the regular security forces. Such groups offset coup risks as substitutes for unreliable regular forces. Similar to other public-private collaborations, they also complement the work of regular forces in providing efficiency and information gains. Finally, these groups distance the government from the controversial use of force. These traits suggest that militias are not simply a sign of failed states or a precursor to a national military, but an important component of security portfolios in many contexts. Using cross-national data (1981–2005), we find support for this mix of incentives. From the perspective of delegation, used to analyze organizational design, global accountability, and policy choices, the domestic and international incentives for governments to choose militias raise explicit governance and accountability issues for the international community.

public-private sector cooperation, conflict, accountability, civil war, militias, domestic

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conflict, human rights, domestic, civil war, militias

Governments, Informal Links to Militias, and Accountability | Sabine Carey, Michael Colaresi and Neil Mitchell | Journal of Conflict Resolution | 2015

conflict, human rights, domestic, civil war, militias

Abstract:

From Syria to Sudan, governments have informal ties with militias that use violence against opposition groups and civilians. Building on research that suggests these groups offer governments logistical benefits in civil wars as well as political benefits in the form of reduced liability for violence, we provide the first systematic global analysis of the scale and patterns of these informal linkages. We find over 200 informal state–militia relationships across the globe, within but also outside of civil wars. We illustrate how informal delegation of violence to these groups can help some governments avoid accountability for violence and repression. Our empirical analysis finds that weak democracies as well as recipients of financial aid from democracies are particularly likely to form informal ties with militias. This relationship is strengthened as the monitoring costs of democratic donors increase. Out-of-sample predictions illustrate the usefulness of our approach that views informal ties to militias as deliberate government strategy to avoid accountability.

conflict, human rights, domestic, civil war, militias

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civil war, democratization, rivalry

With Friends Like These, Who Needs Democracy? The Effects of Transnational Support from Rivals on Post-Conflict Democratization | Michael Colaresi | Journal of Peace Research | 2014

civil war, democratization, rivalry

Abstract:

Previous research has uncovered only ambiguous evidence of the mechanisms that support or inhibit democratic trajectories in the aftermath of civil war. Here I suggest that one specific form of transnational aid during a civil war may have reverberating consequences after the fighting stops. Specifically, when a state emerges to control the executive after a conflict with the help of a previous interstate enemy, the leadership is vulnerable to political attacks on their patriotism and judgment. As such, open democracy becomes a less attractive option for these executives. I investigate this proposition using difference-in-difference matching estimation, as well as several alternative specifications. The findings strongly suggest the presence of disincentives to democratize for those executives that received help from external rivals. This research provides a new set of tools for identifying the causes and potential remedies to deficient democracy after civil wars.

civil war, democratization, rivalry

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Safe Across The Border: The Continued Significance of the Democratic Peace When Controlling for Stable Borders | Johann Park and Michael Colaresi | International Studies Quarterly | 2014

Abstract:

We investigate the research findings reported in Gibler (2007) that suggest the democratic peace is in fact a spurious artifact of stable borders. If corroborated, this set of findings would mark an important reorientation for the field. However, we show that the research design used in Gibler (2007) suffers from several problems, including omitting the lower order terms of interaction variables and inappropriately assuming cross‐dyad independence of artificially created dyadic democracy scores. Our replication and extension shows that even when controlling for stable border variables, democracy continues to be a consistently useful predictor of international conflict. Further, the stable border variables themselves prove to be less consistent predictors of both peace and democracy as compared to previous research. These results suggest that both territorial issues and democracy can coexist as explanations for interstate bellicosity.

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A Boom with Review: How Retrospective Oversight Increases The Foreign Policy Ability of Democracies | Michael Colaresi | American Journal of Political Science | 2012

Abstract:

In the ongoing debate concerning whether democracies can carry out effective national security policy, the role of transparency costs has received little attention. I argue for a more nuanced understanding of how some democracies that possess specific investigative institutions, such as national security–relevant freedom of information laws, legislative oversight powers, and press freedoms, are able to avoid the problems of which democracy skeptics warn. Using a new dataset on national security accountability institutions in democracies within a Bradley‐Terry framework, I find that national security oversight mechanisms raise the probability that a democracy wins international disputes as well as increasing the expected number of enemy casualties, as compared to democracies that lack effective oversight. Contra previous theories of foreign policy efficacy, I find that the chances for democratic foreign policy success are maximized when competitive elections are linked to institutions that increase the retrospective revelation of previously classified information.

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How To Analyze Political Attention With Minimal Assumptions and Costs | Kevin Quinn, Burt Monroe, Michael Colaresi, Michael Crespin and Dragomir Radev | American Journal of Political Science | 2010

Abstract:

Previous methods of analyzing the substance of political attention have had to make several restrictive assumptions or been prohibitively costly when applied to large-scale political texts. Here, we describe a topic model for legislative speech, a statistical learning model that uses word choices to infer topical categories covered in a set of speeches and to identify the topic of specific speeches. Our method estimates, rather than assumes, the substance of topics, the keywords that identify topics, and the hierarchical nesting of topics. We use the topic model to examine the agenda in the U.S. Senate from 1997 to 2004. Using a new database of over 118,000 speeches (70,000,000 words) from the Congressional Record, our model reveals speech topic categories that are both distinctive and meaningfully interrelated and a richer view of democratic agenda dynamics than had previously been possible.

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Fightin' Words: Lexical Feature Selection & Evaluation for Identifying Content of Political Conflict | Burt Monroe, Michael Colaresi and Kevin Quinn | Political Analysis | 2009

Abstract:

Entries in the burgeoning "text-as-data" movement are often accompanied by lists or visualizations of how word (or other lexical feature) usage differs across some pair or set of documents. These are intended either to establish some target semantic concept (like the content of partisan frames) to estimate word-specific measures that feed forward into another analysis (like locating parties in ideological space) or both. We discuss a variety of techniques for selecting words that capture partisan, or other, differences in political speech and for evaluating the relative importance of those words. We introduce and emphasize several new approaches based on Bayesian shrinkage and regularization. We illustrate the relative utility of these approaches with analyses of partisan, gender, and distributive speech in the U.S. Senate.

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The Dynamics of Reciprocity, Accountability, and Credibility | Patrick Brandt, Michael Colaresi and John Freeman | The Journal of Conflict Resolution | 2008

Abstract:

Do public opinion dynamics play an important role in understanding conflict trajectories between democratic governments and other rival groups? The authors interpret several theories of opinion dynamics as competing clusters of contemporaneous causal links connoting reciprocity, accountability, and credibility. They translate these clusters into four distinct Bayesian structural time series models fit to events data from the Israeli-Palestinian conflict with variables for U.S. intervention and Jewish public opinion about prospects for peace. A credibility model, allowing Jewish public opinion to influence U.S., Palestinian, and Israeli behavior within a given month, fits best. More pacific Israeli opinion leads to more immediate Palestinian hostility toward Israelis. This response's direction suggests a negative feedback mechanism in which low-level conflict is maintained and momentum toward either all-out war or dramatic peace is slowed. In addition, a forecasting model including Jewish public opinion is shown to forecast ex ante better than a model without this variable.

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To Kill or to Protect: Security Forces, Domestic Institutions, and Genocide | Michael Colaresi and Sabine Carey | The Journal of Conflict Resolution | 2008

Abstract:

Contemporary studies of genocide have found military capabilities to be inconsistent predictors of state-sponsored killings. We suggest that these empirical inconsistencies stem from the fact that government strength can serve two opposing purposes. Some level of armed capabilities is necessary for a state to remain viable and to provide internal and external security. Yet armed government personnel can be deployed to repress and destroy segments of the public. We identify conditions under which an executive is more likely to use security forces for private-interest killing rather than public protection. We hypothesize that unconstrained leaders are more likely to use their putative security forces to initiate genocide and remain in power. An analysis of state failures that lead to genocide robustly supports the idea that the effect of increased security forces on the risk of genocide is conditional on institutional executive constraints.

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The Benefit of the Doubt: Testing an Informational Theory of the Rally Effect | Michael Colaresi | International Organization | 2007

Abstract:

In this article I investigate the apparent tension between liberal theories that highlight the foreign policy benefits of domestic accountability and the observation that the public tends to reflexively support a leader during an international crisis. Previous theories of the process by which the public rallies around their lead tend to highlight the emotional and automatic nature of citizens' responses to threats. Using a simple signaling model, I show that the political and operational circumstances that increase the probability of post hoc verification and punishment for privately motivated policy enhance the credibility of a leader's choices and transmit information on the benefits of action to the public. I derive several observable hypotheses from the informational model, linking the costliness of the signal, the presence of divided government, election years, active term limits, political insecurity, change in freedom of information laws, and trust in government to the size of the rally in the United States. A battery of empirical tests offer strong support for the information model and suggest that a public rally is a rational response to numerous international crisis circumstances. Observing a rally need not imply an emotional or irrational public.

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Alliances, Arms Buildups and Recurrent Conflict: Testing a Steps-to-War Model | Michael Colaresi and William R. Thompson | Journal of Politics | 2005

Abstract:

Alliances and arms races have received considerable attention in the causes-of-war literature. While a large amount of empirical research has pursued these topics separately, multivariate conditional combinations of these processes have been relatively scarce to date. An argument for doing so is provided by Vasquez’s steps-to-war theory which organizes international relations into an interactive complex of factors, including territorial disputes, interstate rivalry, recurrent crises, alliances, military buildups, and war onset. A model linking indicators of these processes is developed and tested for the 1919–95 era. Substantial empirical support for their interactions emerges. Territorial disputes in the context of rivalry and recurrent crises, aggravated by military buildups and asymmetrical external alliance situations, combine to make escalations to war more probable. Hopefully, an improved understanding of interstate escalatory dynamics can serve as a foundation and stimulus for more interactive attempts to unravel the puzzle of war causation.

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Aftershocks: Post-War Leadership Tenure, Rivalry, and Regime Dynamics | Michael Colaresi | International Studies Quarterly | 2004

Abstract:

Under what conditions are leaders replaced after a war? Past research has reported that the outcome of the war and regime type affect postwar leadership tenure. Yet, this does not exhaust the conditions that could potentially influence political survival. In this article, I reexamine the links between regime type and leadership replacement after a war. I show that past research has failed to account for the dynamics of political leadership, and in the process has misrepresented the evidence supporting previous theories. I then show, using event history techniques, that both internal and external factors can alter leadership trajectories after a war. Specifically, war outcomes significantly affect the job security of a leader outside of international rivalry, but have less of an effect within rivalry. Additionally, relaxing various assumptions concerning the relationship between leadership survival and regime type leads to a richer understanding of the process of postwar leadership turnover. Finally, several propositions concerning the interaction between regime type and the costs of war are not supported in this analysis.

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When Doves Cry: Unreciprocated Cooperation and Leadership Tenure | Michael Colaresi | American Journal of Political Science | 2004

Abstract:

Varied research traditions suggest that dovish leaders will be thrown out of office under harsh external circumstances. Below, I elaborate a model of rivalry maintenance that draws on and refines the insight from studies of leadership tenure and foreign policy. Specifically, I expect a leader who offers unreciprocated cooperation to a rival (a dove) to be more likely to be deselected from power than a leader that takes a harder line vis-a-vis the rival (a hawk). I test this expectation using event history techniques and data spanning the 1950-1990 time period and find strong evidence that dovish leaders pay an electoral price within a rivalry context. The findings suggest an internationally contingent domestic incentive to maintain rivalry and conflict over time.

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The Democracy-Economic Development Nexus: Does The Outside World Matter? | Michael Colaresi and William R. Thompson | Comparative Political Studies | 2003

Abstract:

The relationship between economic development and democratization offers a central focus in linking comparative and international politics. Analysts agree that economic development facilitates democratization but that the relationship is considerably less than perfect. Should advocates of the democratic peace argument prove to be correct in emphasizing the role of regime type in pacifying international politics, an obvious question becomes, What else drives democratization besides economic development? In this article, the authors explore the relationship between domestic development, in the form of economic growth and democratization, and international conditions. They suggest that a number of international factors, such as external threat, conflict, and trade openness, can aid or abet democratization and economic growth. To systematically analyze one facet of this proposition they use both robust regression and generalized estimating equations and find that the international environment significantly alters democracy. External threats from other states tend to decrease democracy.

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Hot Spots or Hot Hands: Serial Crisis Behavior, Escalating Risks, and Strategic Rivalry | Michael Colaresi and William R. Thompson | Journal of Politics | 2002

Abstract:

Recently, a debate has begun concerning the relationship between conflict events over time be- tween the same disputants. While research on rivalries and recurrent conflict suggest that crises are related over time, others (Gartzke and Simon 1999) doubt the empirical and theoretical foundations of this research. We agree with the critics that the proposition that conflicts between adversaries are related over time remains only weakly substantiated. To fill this lacuna, we test four hypotheses relating past crisis behavior and sequences to subsequent conflict, using International Crisis Behavior (ICB) project data. Our results support the serial crisis hypothesis and suggest that the probability of subsequent crises and wars increase with each past crisis. Our findings also reinforce the inclination to give more emphasis to the analysis of rivalries.

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Strategic Rivalries, Protracted Conflict, and Crisis Escalation | Michael Colaresi and William R. Thompson | Journal of Peace Research | 2002

Abstract:

Underlying the emerging interest in the role of rivalry processes as antecedents to interstate conflict is the simple idea that conflict within the constraints of rivalry works differently than conflict outside of rivalry. In this article, we inspect the concepts of protracted conflict, as developed within the Inter- national Crisis Behavior (ICB) project, and rivalry, and discuss some of their applications to crisis escalation. The protracted conflict and rivalry concepts are not identical, but they do overlap in terms of their emphases on historical context, serious goal incompatibilities, and stakes that might be resolved coercively. Developing an argument for the concept of rivalry possessing fewer limitations than protracted conflict, we proceed to analyze and test the interaction between rivalry and other variables, again making use of an ICB escalation model, when predicting crisis escalation to war. Throughout, our basic question concerns what role interstate rivalry plays in crisis behavior. Are the crises of rivals more lethal than those of non-rivals? If so, can we pinpoint why that is the case? We find that rivalry not only makes escalation more likely, but also significantly interacts with more traditional predictors of conflict, such as capability ratios, the number of actors in a crisis, democracy, and the issues under contention.

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Holy Trinities, Rivalry Termination, and Conflict | Derekh Cornwell and Michael Colaresi | International Interactions | 2002

Abstract:

In this article we attempt to correct a number of gaps in the current literature on strategic rivalry. First, we argue that liberal and realist theories of conflict and cooperation have been generally ignored by scholars engaged in rivalry research. Secondly, we argue that current rivalry research fails to disentangle termination processes from conflict within rivalries, mainly due to problems with common operationalizations of rivalry. To bridge these gaps, we test the effects of liberal variables—manifested in the Kantian tripod (democracy, interdependence, and IGO membership)—and what we more loosely term the realist tripod (bipolarity, shared threat, and capability balance) on both rivalry termination and the probability that rivals will engage in a militarized conflict. We conduct this test utilizing a new data set of strategic rivalries compiled by Thompson (1999, 2001) which corrects the tautological operationalization of rivalry commonly used in rivalry research when conflict is the dependent variable. Overall, our results paint a variegated picture, underscoring the importance of rivalry as a special class of dyadic relationship. While realist variables better explain rivalry termination, the direction is opposite that predicted by some realist hypotheses; among liberal variables, only democracy is a robust predictor of both termination and conflict.

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Shocks to the System: Great Power Rivalry and the Leadership Long Cycle | Michael Colaresi | Journal of Conflict Resolution | 2001

Abstract:

The different phases of the leadership long cycle are hypothesized to significantly alter the number of great power rivalries that terminate and initiate. Specifically, the global war phase is expected to “shock” dyads into and out of rivalry. Bivariate and multivariate event history techniques are used to show that periods of capability deconcentration are associated with increased great power rivalry terminations but not initiations. Furthermore, terminations are less likely to occur during phases of systemic capability concentration than in other periods, as the theory predicts. The expectations concerning rivalry initiations are not supported.