Thesis (Ph. D.)--University of Oregon, 2000. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 54-55). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 104). Also available in electronic version. Access restricted to campus users.

This dissertation examines game-theoretic equilibrium analysis applications to deregulated electricity markets. In particular, three specific applications are discussed: analyzing the competitive effects of ownership of financial transmission rights, developing a dynamic game model considering the ramp rate constraints of generators, and analyzing strategic behavior in electricity capacity markets. In the financial transmission right application, an investigation is made of how generators’ ownership of financial transmission rights may influence the effects of the transmission lines on competition. In the second application, the ramp rate constraints of generators are explicitly modeled using a dynamic game framework, and the equilibrium is characterized as the Markov perfect equilibrium. Finally, the strategic behavior of market participants in electricity capacity markets is analyzed and it is shown that the market participants may exaggerate their available capacity in a Nash equilibrium. It is also shown that the more conservative the independent system operator’s capacity procurement, the higher the risk of exaggerated capacity offers. / text

A comprehensive approach is conducted to better utilize dynamic traffic assignment (DTA) in transportation planning by investigating its role in: (1) high-order functions, (2) project evaluation, and (3) traffic assignment. A method is proposed to integrate DTA and the four-step planning model such that traffic assignment is conducted at the subnetwork level while the feedback process occurs at the regional level. By allowing interaction between the subnetwork and regional area, the method is shown to be more beneficial than previous integration structures. Additionally, DTA is applied to a case study involving the proposed urban rail system in Austin, TX. The case study showcases the benefits and capabilities of DTA when analyzing traffic impacts caused by transit rail facilities. Multiple equilibria are shown to arise in simulation-based DTA models due to simplified fundamental diagrams. Piecewise linear diagrams are introduced to eliminate unlikely equilibria. Game theory is also applied to DTA; it is shown that an equilibrium solution is guaranteed to exist for general networks in mixed strategies, and unrealistic equilibria are reduced using the trembling hand refinement. / text

War is an inefficient outcome and therefore states ought to prefer to bargain over areas of conflict instead of fighting. However, in the anarchy of international relations there is no actor with a monopoly of power to enforce contracts between states. States then face a commitment problem when bargaining to prevent war. This dissertation explores three models where this commitment problem can lead to war. The first chapter presents a model that allows for shifts in the distribution of power which play out over an arbitrary number of time periods. This leads to a sufficient condition that implies war under a broader set of conditions than previously shown in the literature. This condition implies that preventive war may be caused by relatively slow, but persistent shifts in the distribution of power. As theorized in power transition theory, differential rates of economic growth can potentially cause war under this mechanism. Relaxing the unitary actor assumption of the first chapter, the second chapter analyzes how the domestic institutional structure of countries affects the likelihood of war. We model institutional divergence by comparing an infinitely lived dictatorship to a democracy with a replaceable leader and allow a range of leader incentives within these institutional frameworks. We show that dictators, even welfare maximizing ones, may lead to war if the initial distribution of resources is highly imbalanced whereas a democracy with a forward looking electorate is always peaceful. Yet when a democratic electorate is myopic, preventive war may result. Political parties act as a mechanism to prevent this outcome. In the third chapter, I investigate adding a third actor to the bargaining model of war. In a static setting, the model uses a notion of cooperative stability to predict balancing and bandwagoning behavior in alliance formation. When extended to a dynamic setting, changes to the system that result in alliance shifting may cause war. Additionally, alliance formation need not correspond to the static solutions, suggesting that the dynamics of power are as important as the distribution of power in alliance formation. / text

published_or_final_version / Mathematics / Master / Master of Philosophy

Groups often find themselves in a position to self-govern: sometimes a formal governing apparatus is weak or nonexistent; sometimes the legal system is underdeveloped, heavily back-logged or inapplicable; and sometimes groups simply have a preference for informal processes. In such cases, contrary to the Hobbesian vision of a self-help nightmare, groups often fare remarkably well both cooperating internally and coexisting with other groups. Diffuse punishment institutions induce cooperation well in tight-knit groups: the theory is well-understood and empirical examples abound. In many realistic settings, though, groups are imperfectly tight-knit, especially when populations are large or sparse or when communications technology is poor (even Facebook networks with very low-cost links are incomplete). Here I relate cooperation to a group's exact structure of communication to identify the role that networks play in making or breaking cooperation. By generalizing the game-theoretic model in Fearon and Laitin (1996), I present a model flexible enough to account for the various ways that a group may be imperfectly tight-knit. / Government

This dissertation presents three independent essays. Chapter 1, which is joint work with Mira Frick, studies a model of innovation adoption by a large population of long-lived consumers who face stochastic opportunities to adopt an innovation of uncertain quality. We study how the potential for social learning in an economy affects consumers' informational incentives and how these in turn shape the aggregate adoption dynamics of an innovation. For a class of Poisson learning processes, we establish the existence and uniqueness of equilibria. In line with empirical findings, equilibrium adoption patterns are either S-shaped or feature successions of concave bursts. In the former case, our analysis predicts a novel saturation effect: Due to informational free-riding, increased opportunities for social learning necessarily lead to temporary slow-downs in learning and do not produce welfare gains. / Economics

published_or_final_version / abstract / toc / Physics / Master / Master of Philosophy

Mathematical models with fixed parameters have a long history of use in describing the dynamics of populations in ecological interactions. However, in many instances, evolutionary changes in species characteristics can have a significant influence on these dynamics. Using evolutionary game theory, we incorporate evolution into population dynamic models and apply the resulting “Darwinian dynamic” models to study the effects that evolutionary changes can have on populations in several ecological scenarios. We start with a single species (Chapter 2), then add a competitor (Chapter 3), and a predator (Chapter 4). In Chapter 2, a rigorous mathematical analysis of the Darwinian logistic model for a single species shows that stable equilibria occur at strategies that maximize population size rather than growth rate. We apply this model to the data obtained from an experimental study on genetically perturbed populations of the flour beetle Tribolium castaneum. In Chapter 3, we apply a Darwinian dynamic modification of the Lotka-Volterra model to investigate circumstances under which evolution will change expected competitive outcomes. We compare the results of our Darwinian Lotka-Volterra model to studies in which unusual observations were made in studies of the flour beetles T. castaneum and T. confusum, including a reversal in the “winner” of competitive exclusion, and evolution from exclusion to coexistence. Chapters 2 and 3 provide one of the few examples in which evolutionary game theory has been successfully applied to empirical data. From a foundation provided by the Darwinian logistic equation, we build Darwinian dynamic models with two and three trophic levels to study effects of evolution on some basic ecological interactions in Chapter 4. We show how a consumer can cause a resource (producer) species to evolve to a mean strategy that increases its growth rate rather than its population size. We also briefly study how predation on the consumer species can affect equilibrium strategies of species lower in the food chain. Our results show how evolutionary game theoretic methods can be useful for studying both theoretical and applied problems that arise due to evolutionary processes, even when they occur on a ecological time scale. They provide a foundation for the future study of evolutionary effects in larger complex networks of interacting species.