This dissertation studies forward looking in dynamic choice. In the first chapter, we propose a dynamic choice model for an error-prone decision maker choosing among risky options. Our axioms yield a representation of the decision maker’s behavior in which the decision maker rationally anticipates her future mistakes, and might be averse to making choices. The resulting model provides a natural welfare criterion even though the decision maker makes mistakes. We introduce comparative measures of error-proneness and choice attitude. We characterize the logit quantal response model as a special case of our model that exhibits constant measure of error-proneness and choice neutrality. We show that different from standard risk, when risk is induced by mistakes, the expected value of a future decision problem might increase even if its options become worse. In the second chapter, we dispense with the assumption of rational anticipation of future mistakes. We propose a model of backward induction with an error-prone decision maker who has limited understanding of her own future choices. To an outside observer, her behavior appears stochastic and her choices become imperfect signals of her payoffs. Our axioms yield a two-parameter representation of the decision maker’s behavior; one parameter characterizes her attitude towards complexity; i.e., her willingness to choose more complicated subtrees over simpler ones, the other her error-proneness. Our model nests fully rational backward induction as a limit of these parameters. We introduce and analyze a measure of complexity aversion and a measure of error-proneness. We show through examples how different decision trees

Mathematical Economics: Topological methods in cardinal utility theory

Essays on Decision Theory

We introduce three definitions. First, we let a "basement" be a set of nodes and actions that supports at least one assessment. Second, we derive from an arbitrary basement its implied "plausibility" (i.e. infinite-relative-likelihood) relation among the game's nodes. Third, we say that this plausibility relation is "additive" if it has a completion represented by the nodal sums of a mass function defined over the game's actions. This last construction is built upon Streufert (2012)'s result that nodes can be specified as sets of actions. Our central result is that a basement has additive plausibility if and only if it supports at least one consistent assessment. The result's proof parallels the early foundations of probability theory and requires only Farkas' Lemma. The result leads to related characterizations, to an easily tested necessary condition for consistency, and to the repair of a nontrivial gap in a proof of Kreps and Wilson (1982).

background

/pdf/additive-plausibility-characterizes-the-supports-of-xlm53zvkx9.pdf

Additive Plausibility Characterizes the Supports of Consistent Assessments

https://link-springer-com-443.webvpn.jmu.edu.cn/content/pdf/10.1007%2F978-94-007-1433-5_20.pdf

Multi-Attribute Approaches to Risk

How to Add Apples and Oranges: Aggregating Performances of Different Nature

This thesis applies game theoretic methods to problems of individual choice and business strategy. It consists of three self-contained chapters. Chapters 2 and 3 explore strategic interaction between agents who are concerned about the social consequences of their actions, while Chapter 4 considers information use by firms who can spy on their competitors. By investigating these diverse topics, the thesis shows how Game Theory can be used to explain and predict outcomes in a variety of real-life scenarios of economic interest. Chapter 2 explores the effect of “other-regarding” preferences on the outcomes of repeated social interactions, modelled as a Prisoner’s Dilemma game. The models of inequality aversion and guilt aversion are identified as compatible with the existing laboratory evidence on the game, and a novel experiment is run to test them against each other. The experiment provided support for the inequality aversion model, which shows that fairness is an important consideration in repeated social interaction. Chapter 3 develops a formal theory of moral choice by proving a representation theorem for guilt-averse preferences. In the chapter, an axiomatic approach is used to deduce a utility function which explains how people trade off material and moral incentives. A novel logarithmic utility is proposed, which is grounded in realistic psychological assumptions and accounts well for the existing body of laboratory evidence. Chapter 4 investigates the welfare consequences of industrial espionage by modelling it as an information acquisition game played by duopolists. In the model, firms can acquire information about unobservable demand either by conducting market research, or by spying on their competitors. The chapter shows how the two information sources affect price and quantity decisions taken by firms. It also shows that aggregate profit and social welfare grow with the precision of the intelligence technology in most environments.

Three Essays in Game Theory

/pdf/mathematical-economics-topological-methods-in-cardinal-3dlbnb78s9.pdf

Mathematical Economics: Topological methods in cardinal utility theory

Citations

Essays on Decision Theory

Additive Plausibility Characterizes the Supports of Consistent Assessments

Multi-Attribute Approaches to Risk

How to Add Apples and Oranges: Aggregating Performances of Different Nature

Three Essays in Game Theory

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