I am an Assistant Professor of Political Science at Trinity College Dublin. Previously, I have been a visiting assistant professor in the department of political science at the University of Rochester (2009-10) and a postdoctoral researcher at ETH Zurich.
I received an M.A. in international politics from the Graduate Institute of International Studies in Geneva (2001-2003), and an M.A. and Ph.D. in political science (world politics) from the University of Michigan (2004-2009). In my dissertation, I studied bargaining models of international negotiations and asked when and why states fail to reach an agreement that would avoid the risks and costs of war.
My current research focuses on the causes of interstate conflict and on their prediction. In particular, I rely on large amounts of fine-grained spatial and temporal data (e.g., newspapers, satellite images, financial markets) to reveal early warning signals for war. I also study the geographic aspects of civil wars. In addition, my interests extend beyond political science to sociology and evolutionary game theory.
Dissertation: "Negotiating Power. Bargaining models of international politics".
Committee: Robert Axelrod (co-chair), James D. Morrow (co-chair), Allan C. Stam,
Barbara Koremenos, Tilman Borgers (UM Economics)
Specialization: International Security, Interstate Wars
Methodology: Game Theory, Bargaining Models, Agent-based Models
Research on international conflict has mostly focused on explaining events such as the onset or termination of wars, rather than on trying to predict them. Recently, however, forecasts of political phenomena have received growing attention. Predictions of violent events, in particular, have been increasingly accurate using various methods ranging from expert knowledge to quantitative methods and formal modeling. Yet, we know little about the limits of these approaches, even though information about these limits has critical implications for both future research and policy-making. In particular, are our predictive inaccuracies due to limitations of our models, data, or assumptions, in which case improvements should occur incrementally. Or are there aspects of conflicts that will always remain fundamentally unpredictable? After reviewing some of the current approaches to forecasting conflict, I suggest avenues of research that could disentangle the causes of our current predictive failures.
Does the recurrence of wars suggest that we fail to recognize dangerous situations for what they are, and are doomed to repeat the errors of the past? Or rather that policymakers correctly anticipate the consequences of their actions but knowingly choose conflict? Unfortunately, little is known about how well wars are anticipated. Do conflicts tend to come as a surprise? I estimated the risk of war as perceived by contemporaries of all interstate and intrastate conflicts between 1816 and 2007. Using historical financial data of government bond yields, I find that market participants tend to underestimate the risk of war prior to its onset, and to react with surprise immediately thereafter. This result illustrates how conflict forecasts can be self-fulfilling or self-defeating. Present predictions may affect future behavior, such that wars may be less likely to occur when they are predicted, but more likely when they are not. I also show that the forecasting record has not improved over the past 200 years, and that wars involving democracies lead to greater market shocks. These findings also have implications for the way decisionmakers respond to new information, and how audiences perceive the risk of war and hence their leaders’ actions.
In 2011–2012 Russia experienced a wave of mass protests surrounding the Duma and presidential elections. The protests, however, faded shortly after the second election. We study the Russian political discourse on Twitter during this period and the main actors involved: the pro-government camp, the opposition, and the general public. We analyze around 700,000 Twitter messages and investigate the social networks of the most active Twitter users. Our analysis shows that pro-government users employed a variety of communication strategies to shift the political discourse and marginalize oppositional voices on Twitter. This demonstrates how authorities can disempower regime critics and successfully manipulate public opinion on social media.
We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.
There have been more than 200 wars since the start of the 20th century, leading to about 35 million battle deaths. However, efforts at forecasting conflicts have so far performed poorly for lack of fine-grained and comprehensive measures of geopolitical tensions. Here, we developed a weekly risk-index by analyzing a comprehensive dataset of historical newspaper articles for 166 countries over the past century, which we then tested on data of all conflicts within and between countries recorded since 1900. Using only information available at the time, we could predict the onset of a war within the next year with up to 85% confidence; we also forecasted over 70% of large-scale wars, while issuing false alarms in only 16% of observations. Predictions were improved up to one year prior to interstate wars, and six months prior to civil wars, giving policy-makers significant additional warning time.
We model an n-player repeated prisoner's dilemma in which players are given traits (e.g., height, age, wealth) which, we assume, affect their behavior. The relationship between traits and behavior is unknown to other players. We then analyze the performance of “prejudiced” strategies—strategies that draw inferences based on the observation of some or all of these traits, and extrapolate the inferred behavior to other carriers of these traits. Such prejudiced strategies have the advantage of learning rapidly, and hence of being well adapted to rapidly changing conditions that might result, for example, from high migration or birth rates. We find that they perform remarkably well, and even systematically outperform both Tit-For-Tat and ALLD when the population changes rapidly.
Students of international relations have long argued that large and rapid shifts in relative power can lead to war. But then why does the rising state not alleviate the concerns of the declining one by reducing its expected future power, so that a commitment problem never emerges? For example, states often limit their ability to launch preemptive attacks by creating demilitarized zones, or they abandon armament programs to avoid preventive wars. In a model of complete information, I show that shifts in power never lead to war when countries can negotiate over the determinants of their power. If war occurs, then, it must be that negotiations over power are impossible or too costly. I then show how third parties, domestic politics, and problems of fungibility can increase the costs of such negotiations, and hence lead to war, even under complete information.
Explaining the emergence and stability of cooperation has been a central challenge in biology, economics and sociology. Unfortunately, the mechanisms known to promote it either require elaborate strategies or hold only under restrictive conditions. Here, we report the emergence, survival, and frequent domination of cooperation in a world characterized by selfishness and a strong temptation to defect, when individuals can accumulate wealth. In particular, we study games with local adaptation such as the prisoner's dilemma, to which we add heterogeneity in payoffs. In our model, agents accumulate wealth and invest some of it in their interactions. The larger the investment, the more can potentially be gained or lost, so that present gains affect future payoffs. We find that cooperation survives for a far wider range of parameters than without wealth accumulation and, even more strikingly, that it often dominates defection. This is in stark contrast to the traditional evolutionary prisoner's dilemma in particular, in which cooperation rarely survives and almost never thrives. With the inequality we introduce, on the contrary, cooperators do better than defectors, even without any strategic behavior or exogenously imposed strategies. These results have important consequences for our understanding of the type of social and economic arrangements that are optimal and efficient.
The onset of interstate conflict often hinges on seemingly random events ('sparks') such as the September 11 2001 attacks or the assassination of Franz Ferdinand on June 28, 1914. However, the literature on the causes of war has mostly focused on identifying fertile grounds ('powder kegs') for interstate conflict, ignoring these intricacies of history that are typically treated as noise and relegated to the error term. Yet, this approach cannot explain why certain fertile grounds never lead to war despite their similarity to others that do, or why wars start precisely when and where they do. In this paper, we aim to show and quantify the importance of these idiosyncratic factors. We obtained information about sparks first from millions of newspaper articles, which we analyzed for signs of growing tensions; and second from government bond yields, which correlate with market participants' expected probability of war. We show that incorporating these proxies for triggers significantly improves our ability to predict and explain conflict. In particular, we find that fertile grounds or the occurrence of a trigger are both prone to conflict, but that it is their combination that is disproportionately dangerous.
Chadefaux, Thomas. What the Enemy Knows: Common Knowledge and the Rationality of War.
Information has played a central role in understanding why international negotiations may break down into costly conflict. Barring indivisibilities or commitment problems, the literature finds that war can only occur between rational unitary actors because of private information about fundamentals such as capabilities, resolve, or costs. I show here, however, that negotiations may fail despite complete information about these fundamentals. All that is needed is for A to not know whether B knows---uncertainty about uncertainty. To ensure peace, then, states need not only know each other's attributes, but also the other's knowledge thereof, and potentially his knowledge of her own knowledge, and so on. Existing models, however, focus on first-order uncertainty and assume common knowledge of information partitions---an unlikely assumption, as states rarely know how much the other knows. This requirement of higher-order complete information illustrates the importance of explicitly incorporating information structures in bargaining models of conflict.
States often bargain over objects that affect their future bargaining power. A large territory, for example, is not only valuable in itself, but also as a source of raw material, population and defense. As a result, states not only try to maximize their benefits when tthey negotiate over the partition of a territory; they also strive to increase their power--their ability to secure a favorable outcome in the future. We study these situations in the context of two- and three-player bargaining games in which present outcomes affect future power, and show three main results: (i) in a two-player negotiation, war never occurs in equilibrium, unless states value the future too differently; (ii) with three players, war can occur in equilibrium; (iii) however, these wars of investments--wars aimed at accumulating resources that improve their ability to secure favorable outcomes in future negotiations--only occur if there are increasing returns in the mapping from resources to the probability of winning.
Work in Progress
Chadefaux, Thomas and Schutte, S. Beyond Elevation: Peripheral Groups, Rough Terrain, and Secessionist Civil War.
Are geographically isolated regions prone to civil war? I explore and test three possible explanations for this relationship. First, isolation may hinder contacts between individuals and hence promote prejudices, discrimination or stereotyping. Second, isolation may reflect an unequal access to wealth or services and hence to increased grievances. Third, isolated regions may be difficult to control by the central state. Unfortunately, lack of fine-grained data has prevented prior research from teasing apart these three explanations. I therefore collected a massive worldwide dataset of most means of transportation, including roads and rails, along with geographical properties including topology and navigable waters, as well as various points of interest such as hospitals, universities and cities. No support was found for the relative deprivation hypothesis nor for the contact hypothesis. However, the results strongly support the importance of state reach in the onset of civil war. Isolated regions are prone to war because rebels select into them for the very reason that they are isolated and hence difficult to control by the central government.
Chadefaux, Thomas and Dirk Helbing. (When) Are Geopolitical Tensions Contagious?
Countries are interconnected. Events in one often affect what happens to its neighbors. The Arab Spring, for example, illustrates the dramatic geopolitical interdependencies across borders. It shows that even strong autocracies are not immune to political changes in their neighbors. Similarly, wars sometimes spread to neighboring countries because of alliances ties (e.g., WWI), refugee flows (e.g., Rwanda), or simply because of altered strategic landscapes (e.g., the war in Iraq probably made its neighbors such as Iran more worried they might be “next”). While these spill-over effects along geography or networks (e.g., alliances) have been the subject of much interest and conjecture, we still know little about the impact of geopolitical tensions in one country on its partners (whether geographic or network partners). One difficulty has been that conflicts are rare, but the analysis of spill-over requires a large number of observations to disentangle potentially confounding effects. Here, we propose to study this problem with fine-grained data instead of the traditional data, which is coded as 1 or 0 for each country-year. We extracted data on international tensions from newspapers for every country and every week since 1900. Using this data, we can measure the extent to which a shock in one country affects its interaction partners, the speed at which it spreads and the networks—geography, alliances, regime type—along which it spreads.