Three essays on the economics of conflict and contest

by Sanders, Shane

The first essay develops a simple sequential-move game to characterize the endogeneity of third-party intervention in conflict. We show how a third party’s “intervention technology” interacts with the canonical “conflict technologies” of two rival parties in affecting the sub-game perfect Nash equilibrium outcome. From the perspective of deterrence strategy, we find that it is more costly for a third party to support an ally to deter a challenger from attacking (i.e., to maintain peace), as compared to the alternative case when the third party supports the ally to gain a disputed territory by attacking (i.e., to create war), ceteris paribus. However, an optimally intervening third party can be either “peace-making,” “peace-breaking,” or neither depending on the characteristics of the conflict and the third party’s stake with each of the rival parties.

The second essay develops a simple model to characterize the role that an intervening third party plays in raising the cost of rebellion in an intrastate conflict. Extending the Gershenson-Grossman (2000) framework of conflict in a two-stage game to the case involving outside intervention in a three-stage game, we examine conditions under which an outside party optimally intervenes such that (i) the strength of the rebel group is diminished or (ii) the rebellion is deterred altogether. We also find conditions in which a third party optimally intervenes at a level insufficient to deter rebellion. Such behavior, which improves the incumbent government’s potential to succeed in conflict, is often overlooked in conflict studies evaluating the effectiveness of intervention. One policy implication of the model is that an increase in the strength of inter-governmental trade partnerships increases the likelihood that third-party intervention acts to deter rebellion.

In the final essay, a simple model of a college basketball season is constructed to examine the existence of conference bias in college basketball’s Ratings Percentage Index. Given the nature of the RPI formula and the hierarchical structure of college basketball’s 31 conferences, we expect the RPI to be biased against teams playing a difficult conference schedule. The model verifies that, even in a perfect world where teams play to expectation and can be transitively compared based on revealed performance level, the RPI does not necessarily provide an ordinal mapping from revealed team ability level to the real number line. This result has important implications on NCAA tournament selection and seeding.