r his paper investigates the dynamics of the "wasted vote" phenomenon and Duverger's Law. I construct a theoretical model in order to consider how preelection polls serve to inform the electorate about the relative chances of the candidates and how that information acts over time to decrease the support of the trailing candidate. The results shed light on how public opinion polls can aggregate information in the electorate and coordinate voters on the viable candidates in the election. Specifically, I show that in a Bayesian game model of strategic voting there exist non-Duvergerian equilibria in which all three candidates receive votes (in the limit). These equilibria require extreme coordination, however, and any variation in beliefs leads voters away from them to one of the Duvergerian equilibria. Thus, non-Duvergerian equilibria are unstable, while two-party equilibria are not. In addition, I describe how preelection polls provide information to voters about the viability of candidates and can thus be used by voters to coordinate on a Duvergerian outcome.

We study two different varieties of uncertainty that countries can face in international crises and establish general results about the relationship between these sources of uncertainty and the possibility of peaceful resolution of conflict. Among our results, we show that under some weak conditions, there is no equilibrium of any crisis bargaining game that has voluntary agreements and zero probability of costly war. We also show that while uncertainty about the other side's cost of war may be relatively benign in peace negotiations, uncertainty about the other side's strength in war makes it much more difficult to guarantee peaceful outcomes. Along the way, we are able to assess the degree to which particular modeling assumptions found in the existing literature drive the well-known relationship between uncertainty, the incentive to misrepresent, and costly war. We find that while the theoretical connection between war and uncertainty is quite robust to relaxing many modeling assumptions, whether uncertainty is about costs or the probability of victory remains important.

In this paper, we report the results of a series of experiments on a version of the centipede game in which the total payoff to the two players is constant. Standard backward induction arguments lead to a unique Nash equilibrium outcome prediction, which is the same as the prediction made by theories of "fair" or "focal" outcomes.We find that subjects frequently fail to select the unique Nash outcome prediction. While this behavior was also observed in McKelvey and Palfrey (1992) in the "growing pie" version of the game they studied, the Nash outcome was not "fair" , and there was the possibility of Pareto improvement by deviating from Nash play. Their findings could therefore be explained by small amounts of altruistic behavior. There are no Pareto improvements available in the constant-sum games we examine, hence explanations based on altruism cannot account for these new data.We examine and compare two classes of models to explain this data. The first class consists of non-equilibrium modifications of the standard "Always Take" model. The other class we investigate, the Quanta! Response Equilibrium model, describes an equi librium in which subjects make mistakes in implementing their best replies and assume other players do so as well. One specification of this model fits the experimental data best, among the models we test, and is able to account for all the main features we observe in the data.

We consider rent-seeking contests with two players that each have private information about their own cost of effort. We consider both discrete and continuous distributions of costs and give results for each case, focusing on existence of equilibria.JEL Classification: D72; C72

Working with the definition of mutual optimism as war due to inconsistent beliefs, we formalize the mutual optimism argument to test the theory's logical validity. We find that in the class of strategic situations where mutual optimism is a necessary condition for war-i.e., where war is known to be inefficient, war only occurs if both sides prefer it to a negotiated settlement, and on the eve of conflict war is self-evident-then there is no Bayesian-Nash equilibrium where wars are fought because of mutual optimism. The fundamental reason that mutual optimism cannot lead to war is that if both sides are willing to fight, each side should infer that they have either underestimated the strength of the opponent or overestimated their own strength. In either case, these inferences lead to a peaceful settlement of the dispute. We also show that this result extends to situations in which there is bounded rationality and/or noncommon priors. W hy do states fight costly wars when less costly negotiated settlements are possible? Must there not be some mutually agreeable alternative to war that can produce the same result without incurring the social loss? Could not decision makers agree to distribute the disputed territory or assets in a way consistent with their beliefs about the likely outcome of conflict, saving both sides significant death and destruction? In this article, we address one specific rationalist answer to these questions. As Blainey (1988) intimates, the high hopes on the eve of war suggest a sad conclusion: wars only occur when both rivals believe they can achieve more through fighting than through peaceful means. How might this be so? Obviously, when two countries are involved in a war, if one side wins then the other loses. We might then conclude that at least one side, in particular the loser, would prefer some peaceful method of resolving the dispute if she were certain of the outcome. But war is an uncertain process. Given this uncertainty, the leaders of the two countries must each form expectations about the results of a conflict to guide their decision making. The , as well as other seminar participants. We would also like to thank the editor of the AJPS and two anonymous reviewers for helpful comments. Any remaining errors are our own. Kris Ramsay acknowledges financial support from NSF grant SES-0413381.