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The authors present a model of the relationship between the spread of new military technologies and the occurrence of war. A new technology could shift the balance of power, causing anticipatory war as one side tries to prevent the other from obtaining it. When one side already has it, war is more likely when the shift in power is large, likely, and durable. When neither side has it, war is more likely when the expected shift is asymmetric (e.g., one side is more likely to get it) and when the two sides fear that a war will occur once one of them has it. The authors illustrate the model with historical examples from the spread of firearms (the Musket Wars in precolonial New Zealand) and of nuclear weapons (the end of US nuclear monopoly and the 1967 Six-Day War). A broader implication is that major power competition can unintentionally cause wars elsewhere.

We generalize two classes of statistical sequential incomplete information games: (1) those resembling typical signaling games, in which a single agent represents each player, allowing for information to be revealed about future play; and (2) those in which each player is represented by a set of independent agents, where moves do not reveal private information. The generalized model we develop, the Correlated Agent Model, relies on a parameter, r, which denotes the correlation between two agents' private information, i.e. the extent to which a player knows the future private component of her preferences. The independent agent and single agent models are special cases, where r=0 and r=1, respectively. The model also allows 0 < r < 1, a class of games which have not yet been considered. We apply the model to crisis bargaining and demonstrate how to estimate r, as well as parameters associated with utilities. [Reprinted by permission of Sage Publications Ltd., copyright holder.]

We generalize two classes of statistical sequential incomplete information games: (1) those resembling typical signaling games, in which a single agent represents each player, allowing for information to be revealed about future play; and (2) those in which each player is represented by a set of independent agents, where moves do not reveal private information. The generalized model we develop, the Correlated Agent Model, relies on a parameter, ρ, which denotes the correlation between two agents' private information, i.e. the extent to which a player knows the future private component of her preferences. The independent agent and single agent models are special cases, where ρ=0 and ρ=1, respectively. The model also allows 0 < ρ < 1, a class of games which have not yet been considered. We apply the model to crisis bargaining and demonstrate how to estimate ρ, as well as parameters associated with utilities.

We present a simple method for estimating regressions based on recursive extensive-form games. Our procedure, which can be implemented in most standard statistical packages, involves sequentially estimating standard logits (or probits) in a manner analogous to backwards induction. We demonstrate that the technique produces consistent parameter estimates and show how to calculate consistent standard errors. To illustrate the method, we replicate Leblang's (2003) study of speculative attacks by financial markets and government responses to these attacks. Adapted from the source document.

We present a simple method for estimating regressions based on recursive extensive-form games. Our procedure, which can be implemented in most standard statistical packages, involves sequentially estimating standard logits (or probits) in a manner analogous to backwards induction. We demonstrate that the technique produces consistent parameter estimates and show how to calculate consistent standard errors. To illustrate the method, we replicate Leblang's (2003) study of speculative attacks by financial markets and government responses to these attacks.